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Articles in Press
4/18/2024 8:40:11 AM | Browse: 33 | Download: 0
Category |
Pediatrics |
Manuscript Type |
Retrospective Study |
Article Title |
Magnetic resonance imaging scanning susceptibility weighted imaging sequences in the diagnosis and prognostic evaluation of neonatal hypoxic-ischemic encephalopathy
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Manuscript Source |
Unsolicited Manuscript |
All Author List |
Hui Zhao and Hai-Tao Wang |
Funding Agency and Grant Number |
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Corresponding Author |
Hai-Tao Wang, Doctor, Attending Doctor, Department of Medical Imaging, Hanzhong People's Hospital, No. 251 North Tuanjie Street, Hantai District, Hanzhong 723000, Shaanxi Province, China. g8j931@163.com |
Key Words |
Hypoxic-ischemic encephalopathy; Neonate; Diagnostic efficacy |
Core Tip |
Susceptibility weighted imaging (SWI) sequences in magnetic resonance imaging scanning potentially provide richer and more detailed imaging information for neonatal hypoxic-ischemic encephalopathy, facilitating early and accurate diagnosis. In prognostic evaluation, SWI reveals pathological changes related to neurological outcomes, providing essential guidance for clinical decision-making and expectations for patient families. However, interpreting SWI images requires integration with clinical manifestations and other imaging indicators to ensure diagnostic accuracy. |
Citation |
Zhao H, Wang HT. Magnetic resonance imaging scanning susceptibility weighted imaging sequences in the diagnosis and prognostic evaluation of neonatal hypoxic-ischemic encephalopathy. World J Clin Cases 2024; In press |
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Received |
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2024-02-22 05:17 |
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Peer-Review Started |
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2024-02-22 05:17 |
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To Make the First Decision |
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Return for Revision |
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2024-04-04 08:30 |
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Revised |
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2024-04-09 11:47 |
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Second Decision |
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2024-04-18 02:37 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Company Editor-in-Chief |
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2024-04-18 08:40 |
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Articles in Press |
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2024-04-18 08:40 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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ISSN |
2307-8960 (online) |
Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/ |
Copyright |
© The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved. |
Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
Website |
http://www.wjgnet.com |
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