A framework to measure myocardial extracellular volume fraction using dual-phase low dose CT images

Authors

  • Liu Yixun,

    Corresponding author
    1. Clinical Image Processing Service, Radiology and Imaging Sciences, NIH Clinical Center, Bethesda, Maryland 20892
    • Author to whom correspondence should be addressed. Electronic mail: JYao@cc.nih.gov; Telephone: 301.402.3225.

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  • Liu Songtao,

    1. Radiology and Imaging Sciences, NIH Clinical Center, Bethesda, Maryland 20892-1182 and Molecular Biomedical Imaging Laboratory, National Institute of Biomedical Imaging and Bioengineering, NIH Clinical Center, Bethesda, Maryland 20892
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    • a)

      Y. Liu and S. Liu contributed equally to this work.

  • Nacif Marcelo S.,

    1. Radiology and Imaging Sciences, NIH Clinical Center, Bethesda, Maryland 20892-1182
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  • Sibley Christopher T.,

    1. Radiology and Imaging Sciences, NIH Clinical Center, Bethesda, Maryland 20892-1182 and Molecular Biomedical Imaging Laboratory, National Institute of Biomedical Imaging and Bioengineering, NIH Clinical Center, Bethesda, Maryland 20892
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  • Bluemke David A.,

    1. Radiology and Imaging Sciences, NIH Clinical Center, Bethesda, Maryland 20892-1182 and Molecular Biomedical Imaging Laboratory, National Institute of Biomedical Imaging and Bioengineering, NIH Clinical Center, Bethesda, Maryland 20892
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  • Summers Ronald M.,

    1. Clinical Image Processing Service, Radiology and Imaging Sciences, NIH Clinical Center, Bethesda, Maryland 20892
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  • Yao Jianhua

    1. Clinical Image Processing Service, Radiology and Imaging Sciences, NIH Clinical Center, Bethesda, Maryland 20892
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    • a)

      Y. Liu and S. Liu contributed equally to this work.


Abstract

Purpose:

Myocardial extracellular volume fraction (ECVF) is a surrogate imaging biomarker of diffuse myocardial fibrosis, a hallmark of pathologic ventricular remodeling. Low dose cardiac CT is emerging as a promising modality to detect diffuse interstitial myocardial fibrosis due to its fast acquisition and low radiation; however, the insufficient contrast in the low dose CT images poses great challenge to measure ECVF from the image.

Methods:

To deal with this difficulty, the authors present a complete ECVF measurement framework including a point-guided myocardial modeling, a deformable model-based myocardium segmentation, nonrigid registration of pre- and post-CT, and ECVF calculation.

Results:

The proposed method was evaluated on 20 patients by two observers. Compared to the manually delineated reference segmentations, the accuracy of our segmentation in terms of true positive volume fraction (TPVF), false positive volume fraction (FPVF), and average surface distance (ASD), were 92.18% ± 3.52%, 0.31% ± 0.10%, 0.69 ± 0.14 mm, respectively. The interobserver variability measured by concordance correlation coefficient regarding TPVF, FPVF, and ASD were 0.95, 0.90, 0.94, respectively, demonstrating excellent agreement. Bland-Altman method showed 95% limits of agreement between ECVF at CT and ECVF at MR.

Conclusions:

The proposed framework demonstrates its efficiency, accuracy, and noninvasiveness in ECVF measurement and dramatically advances the ECVF at cardiac CT toward its clinical use.

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