Evidence map›Paper›PMID 40604294›Full record

ArticleNpj imaging2024

Ultrahigh-field animal MRI system with advanced technological update.

Yaohui Wang, Guyue Zhou, Haoran Chen, Pengfei Wu, Wenhui Yang, Feng Liu, Qiuliang Wang

Abstract read
In one paragraph

Article in Npj imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yaohui WangInstitute of Electrical Engineering, Chinese Academy of Sciences, Beijing, 100190, China. yhw@mail.iee.ac.cn.
Guyue ZhouSchool of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China.
Haoran ChenSchool of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China.
Pengfei WuInstitute of Electrical Engineering, Chinese Academy of Sciences, Beijing, 100190, China.
Wenhui YangInstitute of Electrical Engineering, Chinese Academy of Sciences, Beijing, 100190, China.
Feng LiuSchool of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, QLD, 4072, Australia.
Qiuliang WangInstitute of Electrical Engineering, Chinese Academy of Sciences, Beijing, 100190, China. qiuliang@mail.iee.ac.cn.

Funding

International Partnership Program of Chinese Academy of Sciences 182111KYSB20210014National Natural Science Foundation of China 52293423
6 · The paper itself

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.

Identifiers

PMID40604294
PMCPMC12118741

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.