In vivo imaging of phosphocreatine with artificial neural networks

Lin Chen, Michael Schär, Kannie W. Y. Chan, Jianpan Huang, Zhiliang Wei, Hanzhang Lu, Qin Qin, Robert G. Weiss, Peter C. M. van Zijl and Jiadi Xu ()
Additional contact information
Lin Chen: Kennedy Krieger Research Institute
Michael Schär: The Johns Hopkins University School of Medicine
Kannie W. Y. Chan: The Johns Hopkins University School of Medicine
Jianpan Huang: City University of Hong Kong
Zhiliang Wei: Kennedy Krieger Research Institute
Hanzhang Lu: Kennedy Krieger Research Institute
Qin Qin: Kennedy Krieger Research Institute
Robert G. Weiss: The Johns Hopkins University School of Medicine
Peter C. M. van Zijl: Kennedy Krieger Research Institute
Jiadi Xu: Kennedy Krieger Research Institute

Nature Communications, 2020, vol. 11, issue 1, 1-10

Abstract: 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

Date: 2020
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DOI: 10.1038/s41467-020-14874-0

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