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Cardiac SPECT radiomic features repeatability and reproducibility: A multi-scanner phantom study

  • ORIGINAL ARTICLE
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Journal of Nuclear Cardiology Aims and scope

Abstract

Background

The aim of this work was to assess the robustness of cardiac SPECT radiomic features against changes in imaging settings, including acquisition, and reconstruction parameters.

Methods

Four commercial SPECT and SPECT/CT cameras were used to acquire images of a static cardiac phantom mimicking typical myorcardial perfusion imaging using 185 MBq of 99mTc. The effects of different image acquisition and reconstruction parameters, including number of views, view matrix size, attenuation correction, as well as image reconstruction related parameters (algorithm, number of iterations, number of subsets, type of post-reconstruction filter, and its associated parameters, including filter order and cut-off frequency) were studied. In total, 5,063 transverse views were reconstructed by varying the aforementioned factors. Eighty-seven radiomic features including first-, second-, and high-order textures were extracted from these images. To assess reproducibility and repeatability, the coefficient of variation (COV), as a widely adopted metric, was measured for each of the radiomic features over the different imaging settings.

Results

The Inverse Difference Moment Normalized (IDMN) and Inverse Difference Normalized (IDN) features from the Gray Level Co-occurrence Matrix (GLCM), Run Percentage (RP) from the Gray Level Co-occurrence Matrix (GLRLM), Zone Entropy (ZE) from the Gray Level Size Zone Matrix (GLSZM), and Dependence Entropy (DE) from the Gray Level Dependence Matrix (GLDM) feature sets were the only features that exhibited high reproducibility (COV ≤ 5%) against changes in all imaging settings. In addition, Large Area Low Gray Level Emphasis (LALGLE), Small Area Low Gray Level Emphasis (SALGLE) and Low Gray Level Zone Emphasis (LGLZE) from GLSZM, and Small Dependence Low Gray Level Emphasis (SDLGLE) from GLDM feature sets turned out to be less reproducible (COV > 20%) against changes in imaging settings. The GLRLM (31.88%) and GLDM feature set (54.2%) had the highest (COV < 5%) and lowest (COV > 20%) number of the reproducible features, respectively. Matrix size had the largest impact on feature variability as most of the features were not repeatable when matrix size was modified with 82.8% of them having a COV > 20%.

Conclusion

The repeatability and reproducibility of SPECT/CT cardiac radiomic features under different imaging settings is feature-dependent. Different image acquisition and reconstruction protocols have variable effects on radiomic features. The radiomic features exhibiting low COV are potential candidates for future clinical studies.

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Abbreviations

SPECT:

Single-photon emission computed tomography

COV:

Coefficient of variation

GLCM:

Gray level co-occurrence matrix

GLRLM:

Gray level co-occurrence matrix

GLSZM:

Gray level size zone matrix

GLDM:

Gray level dependence matrix

IDMN:

Inverse difference moment normalized

LALGLE:

Large area low gray level emphasis

SALGLE:

Small area low gray level emphasis

SDLGLE:

Small dependence low gray level emphasis

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Acknowledgments

This work was supported by the Swiss National Science Foundation under grant SNFN 320030_176052.

Disclosure

Mohammad Edalat-Javid, Isaac Shiri, Ghasem Hajianfar, Hamid Abdollahi, Hossein Arabi, Niki Oveisi, Mohammad Javadian, Mojtaba Shamsaei Zafarghandi, Hadi Malek, Ahmad Bitarafan-Rajabi, Mehrdad Oveisi, and Habib Zaidi declare that they have no conflict of interest.

Author information

Author notes

  1. Mohammad Edalat-Javid and Isaac Shiri have contributed equally to this manuscript

Authors and Affiliations

  1. Department of Energy Engineering and Physics, Amir Kabir University of Technology, Tehran, Iran

    Mohammad Edalat-Javid MSc & Mojtaba Shamsaei Zafarghandi PhD

  2. Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, 1211, Geneva 4, Switzerland

    Isaac Shiri MSc, Hossein Arabi PhD & Habib Zaidi PhD

  3. Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Science, Tehran, Iran

    Ghasem Hajianfar MSc, Hadi Malek MD, Ahmad Bitarafan-Rajabi PhD & Mehrdad Oveisi PhD

  4. Department of Radiologic Sciences and Medical Physics, Faculty of Allied Medicine, Kerman University, Kerman, Iran

    Hamid Abdollahi PhD

  5. School of Population and Public Health, The University of British Columbia, Vancouver, BC, V6T 1Z4, Canada

    Niki Oveisi MSc

  6. Department of Computer Engineering, Faculty of Information Technology, Kermanshah University of Technology, Kermanshah, Iran

    Mohammad Javadian PhD

  7. Cardiovascular Intervention Research Center, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran

    Ahmad Bitarafan-Rajabi PhD

  8. Echocardiography Research Center, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran

    Ahmad Bitarafan-Rajabi PhD

  9. Department of Computer Science, University of British Columbia, Vancouver, BC, Canada

    Mehrdad Oveisi PhD

  10. Geneva University Neurocenter, Geneva University, 1205, Geneva, Switzerland

    Habib Zaidi PhD

  11. Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands

    Habib Zaidi PhD

  12. Department of Nuclear Medicine, University of Southern Denmark, Odense, Denmark

    Habib Zaidi PhD

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  1. Mohammad Edalat-Javid MSc
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Edalat-Javid, M., Shiri, I., Hajianfar, G. et al. Cardiac SPECT radiomic features repeatability and reproducibility: A multi-scanner phantom study. J. Nucl. Cardiol. 28, 2730–2744 (2021). https://doi.org/10.1007/s12350-020-02109-0

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