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Performance of Radiomics Models Based on Coronary Computed Tomography Angiography in Predicting The Risk of Major Adverse Cardiovascular Events Within 3 Years: A Comparison Between the Pericoronary Adipose Tissue Model and the Epicardial Adipose Tissue Model

  • Hongrui You
    Affiliations
    Jinzhou Medical University General Hospital of Northern Theater Command Postgraduate Training Base, No.83 Wenhua Road, Shenhe District, Shenyang, Liaoning Province, China
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  • Rongrong Zhang
    Affiliations
    Jinzhou Medical University General Hospital of Northern Theater Command Postgraduate Training Base, No.83 Wenhua Road, Shenhe District, Shenyang, Liaoning Province, China
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  • Jiesi Hu
    Affiliations
    General Electric Healthcare, No.1 Tongji south Road, Daxing District, Beijing, China
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  • Yu Sun
    Affiliations
    Department of Radiology, General Hospital of Northern Theater Command, No.83 Wenhua Road, Shenhe District, Shenyang, Liaoning Province, China

    Key Laboratory of Cardiovascular Imaging and Research, No.83 Wenhua Road, Shenhe District, Shenyang, Liaoning Province, China
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  • Xiaogang Li
    Affiliations
    Department of Radiology, General Hospital of Northern Theater Command, No.83 Wenhua Road, Shenhe District, Shenyang, Liaoning Province, China

    Key Laboratory of Cardiovascular Imaging and Research, No.83 Wenhua Road, Shenhe District, Shenyang, Liaoning Province, China
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  • Jie Hou
    Affiliations
    Department of Radiology, General Hospital of Northern Theater Command, No.83 Wenhua Road, Shenhe District, Shenyang, Liaoning Province, China

    Key Laboratory of Cardiovascular Imaging and Research, No.83 Wenhua Road, Shenhe District, Shenyang, Liaoning Province, China
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  • Yusong Pei
    Affiliations
    Department of Nuclear Medicine, General Hospital of Northern Theater Command, No.83 Wenhua Road, Shenhe District, Shenyang, Liaoning Province, China
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  • Lianlian Zhao
    Affiliations
    Jinzhou Medical University General Hospital of Northern Theater Command Postgraduate Training Base, No.83 Wenhua Road, Shenhe District, Shenyang, Liaoning Province, China
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  • Libo Zhang
    Affiliations
    Department of Radiology, General Hospital of Northern Theater Command, No.83 Wenhua Road, Shenhe District, Shenyang, Liaoning Province, China

    Key Laboratory of Cardiovascular Imaging and Research, No.83 Wenhua Road, Shenhe District, Shenyang, Liaoning Province, China
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  • Benqiang Yang
    Correspondence
    Address correspondence to: B.Y.
    Affiliations
    Department of Radiology, General Hospital of Northern Theater Command, No.83 Wenhua Road, Shenhe District, Shenyang, Liaoning Province, China

    Key Laboratory of Cardiovascular Imaging and Research, No.83 Wenhua Road, Shenhe District, Shenyang, Liaoning Province, China
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Published:April 14, 2022DOI:https://doi.org/10.1016/j.acra.2022.03.015

      Rationale and Objectives

      To compare the prediction performance of the epicardial adipose tissue (EAT) and pericoronary adipose tissue (PCAT) radiomics models based on coronary computed tomography angiography for major adverse cardiovascular events (MACE) within 3 years.

      Materials and Methods

      Our study included 288 patients (144 with MACE and 144 without MACE within 3 years) by matching age, gender, body mass index, and medication intake. Patients were randomly assigned either to the training (n = 201) or validation cohort (n = 87). A total of 184 radiomics features were extracted from EAT and PCAT images. Spearman's rank correlation coefficient and the gradient boosting decision tree algorithm were performed for feature selection. Five models were established based on PCAT or EAT radiomics features and clinical factors, including PCAT, EAT, clinical, PCAT-clinical, and EAT-clinical model (MPCAT, MEAT, Mclinical, MPCAT-clinical, and MEAT-clinical). Receiver operating characteristic curves, calibration curves, and the decision curve analysis were plotted to evaluate the model performance.

      Results

      The MPCAT achieved an area under the curve (AUC) of 0.703 in the validation cohort, which was better than MEAT with AUC of 0.538. The MPCAT-clinical showed better performance (AUC = 0.781) in predicting MACE than the Mclinical (AUC = 0.748) or MEAT-clinical (AUC = 0.745).

      Conclusion

      Our results showed that the PCAT was better than the EAT in both single modality and combined models, and the MPCAT-clinical had the most significant clinical value in predicting the occurrence of MACE within 3 years.

      Key Words

      Abbreviations:

      EAT (epicardial adipose tissue), PCAT (pericoronary adipose tissue), CCTA (coronary computed tomography angiography), MACE (major adverse cardiovascular events), CAD (coronary artery disease), FAI (Fat attenuation index), RCA (right coronary artery), AUC (area under the curve), ROI (region of interest), MPCAT (PCAT model), MEAT (EAT model), Mclinical (clinical model), MPCAT-clinical (PCAT-clinical model), MEAT-clinical (EAT-clinical model)
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