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In vivo imaging of phosphocreatine with artificial neural networks

Author

Listed:
  • Lin Chen

    (Kennedy Krieger Research Institute
    The Johns Hopkins University School of Medicine)

  • Michael Schär

    (The Johns Hopkins University School of Medicine)

  • Kannie W. Y. Chan

    (The Johns Hopkins University School of Medicine
    City University of Hong Kong)

  • Jianpan Huang

    (City University of Hong Kong)

  • Zhiliang Wei

    (Kennedy Krieger Research Institute
    The Johns Hopkins University School of Medicine)

  • Hanzhang Lu

    (Kennedy Krieger Research Institute
    The Johns Hopkins University School of Medicine)

  • Qin Qin

    (Kennedy Krieger Research Institute
    The Johns Hopkins University School of Medicine)

  • Robert G. Weiss

    (The Johns Hopkins University School of Medicine
    Johns Hopkins University School of Medicine)

  • Peter C. M. van Zijl

    (Kennedy Krieger Research Institute
    The Johns Hopkins University School of Medicine)

  • Jiadi Xu

    (Kennedy Krieger Research Institute
    The Johns Hopkins University School of Medicine)

Abstract

Phosphocreatine (PCr) plays a vital role in neuron and myocyte energy homeostasis. Currently, there are no routine diagnostic tests to noninvasively map PCr distribution with clinically relevant spatial resolution and scan time. Here, we demonstrate that artificial neural network-based chemical exchange saturation transfer (ANNCEST) can be used to rapidly quantify PCr concentration with robust immunity to commonly seen MRI interferences. High-quality PCr mapping of human skeletal muscle, as well as the information of exchange rate, magnetic field and radio-frequency transmission inhomogeneities, can be obtained within 1.5 min on a 3 T standard MRI scanner using ANNCEST. For further validation, we apply ANNCEST to measure the PCr concentrations in exercised skeletal muscle. The ANNCEST outcomes strongly correlate with those from 31P magnetic resonance spectroscopy (R = 0.813, p

Suggested Citation

  • Lin Chen & Michael Schär & Kannie W. Y. Chan & Jianpan Huang & Zhiliang Wei & Hanzhang Lu & Qin Qin & Robert G. Weiss & Peter C. M. van Zijl & Jiadi Xu, 2020. "In vivo imaging of phosphocreatine with artificial neural networks," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-14874-0
    DOI: 10.1038/s41467-020-14874-0
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