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- Publisher Website: 10.1038/s41467-020-14874-0
- Scopus: eid_2-s2.0-85080085400
- PMID: 32102999
- WOS: WOS:000564293100002
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Article: In vivo imaging of phosphocreatine with artificial neural networks
Title | In vivo imaging of phosphocreatine with artificial neural networks |
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Authors | |
Issue Date | 2020 |
Citation | Nature Communications, 2020, v. 11, n. 1, article no. 1072 How to Cite? |
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 < 0.001, t test). These results suggest that ANNCEST has potential as a cost-effective and widely available method for measuring PCr and diagnosing related diseases. |
Persistent Identifier | http://hdl.handle.net/10722/327982 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Chen, Lin | - |
dc.contributor.author | Schär, Michael | - |
dc.contributor.author | Chan, Kannie W.Y. | - |
dc.contributor.author | Huang, Jianpan | - |
dc.contributor.author | Wei, Zhiliang | - |
dc.contributor.author | Lu, Hanzhang | - |
dc.contributor.author | Qin, Qin | - |
dc.contributor.author | Weiss, Robert G. | - |
dc.contributor.author | van Zijl, Peter C.M. | - |
dc.contributor.author | Xu, Jiadi | - |
dc.date.accessioned | 2023-06-05T06:53:06Z | - |
dc.date.available | 2023-06-05T06:53:06Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Nature Communications, 2020, v. 11, n. 1, article no. 1072 | - |
dc.identifier.uri | http://hdl.handle.net/10722/327982 | - |
dc.description.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 < 0.001, t test). These results suggest that ANNCEST has potential as a cost-effective and widely available method for measuring PCr and diagnosing related diseases. | - |
dc.language | eng | - |
dc.relation.ispartof | Nature Communications | - |
dc.title | In vivo imaging of phosphocreatine with artificial neural networks | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1038/s41467-020-14874-0 | - |
dc.identifier.pmid | 32102999 | - |
dc.identifier.scopus | eid_2-s2.0-85080085400 | - |
dc.identifier.volume | 11 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | article no. 1072 | - |
dc.identifier.epage | article no. 1072 | - |
dc.identifier.eissn | 2041-1723 | - |
dc.identifier.isi | WOS:000564293100002 | - |