Ultrahigh-field animal MRI system with advanced technological update

Yaohui Wang, Guyue Zhou, Haoran Chen, Pengfei Wu, Wenhui Yang, Feng Liu, Qiuliang Wang
{"title":"Ultrahigh-field animal MRI system with advanced technological update","authors":"Yaohui Wang, Guyue Zhou, Haoran Chen, Pengfei Wu, Wenhui Yang, Feng Liu, Qiuliang Wang","doi":"10.1038/s44303-024-00060-0","DOIUrl":null,"url":null,"abstract":"Animal magnetic resonance imaging (MRI) systems typically deliver superior imaging performance over conventional human MRI systems, making them a prevailing instrument in preclinical research. It is challenging to achieve the high performance of these animal MRI systems, due to the multifaceted nature of the various system components and the complexity of integration debugging. This work described the design, fabrication, measurement and integration of a 7 T animal MRI system, which exhibits several performance highlights. Both the magnet and gradient assembly adopted an ultra-shielding strategy, facilitating ease of system installation, maintenance and debugging. The main magnetic field exhibits acceptable homogeneity and stability, and the gradient coil is mechanically reliable thanks to zero-force control. The animal MRI system underwent debugging using proprietary imaging software to generate images of phantoms, fruits and organisms. Further research investigation will be performed to promote more scientific outputs with enhanced functional capabilities.","PeriodicalId":501709,"journal":{"name":"npj Imaging","volume":" ","pages":"1-10"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44303-024-00060-0.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"npj Imaging","FirstCategoryId":"1085","ListUrlMain":"https://www.nature.com/articles/s44303-024-00060-0","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Animal magnetic resonance imaging (MRI) systems typically deliver superior imaging performance over conventional human MRI systems, making them a prevailing instrument in preclinical research. It is challenging to achieve the high performance of these animal MRI systems, due to the multifaceted nature of the various system components and the complexity of integration debugging. This work described the design, fabrication, measurement and integration of a 7 T animal MRI system, which exhibits several performance highlights. Both the magnet and gradient assembly adopted an ultra-shielding strategy, facilitating ease of system installation, maintenance and debugging. The main magnetic field exhibits acceptable homogeneity and stability, and the gradient coil is mechanically reliable thanks to zero-force control. The animal MRI system underwent debugging using proprietary imaging software to generate images of phantoms, fruits and organisms. Further research investigation will be performed to promote more scientific outputs with enhanced functional capabilities.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Stratifying vascular disease patients into homogeneous subgroups using machine learning and FLAIR MRI biomarkers Metabolic nanoscopy enhanced by experimental and computational approaches Ultrahigh-field animal MRI system with advanced technological update Automated analysis of ultrastructure through large-scale hyperspectral electron microscopy Evaluation of the redox alteration in Duchenne muscular dystrophy model mice using in vivo DNP-MRI
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1