Evidence map›Paper›PMID 36312037›Full record

ArticleFrontiers in neuroscience2022

Susceptibility-weighted imaging at high-performance 0.5T magnetic resonance imaging system: Protocol considerations and experimental results.

Yueqi Qiu, Haoran Bai, Hao Chen, Yue Zhao, Hai Luo, Ziyue Wu, Zhiyong Zhang

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Advancements in MRI application in the morphological development of fetal cerebral venous system: a review.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2025
    Review
  3. Review
  4. Review
  5. Article
  6. Review
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.

Yueqi QiuSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Haoran BaiSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Hao ChenSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Yue ZhaoWuxi Marvel Stone Healthcare Co., Ltd., Wuxi, Jiangsu, China.
Hai LuoWuxi Marvel Stone Healthcare Co., Ltd., Wuxi, Jiangsu, China.
Ziyue WuWuxi Marvel Stone Healthcare Co., Ltd., Wuxi, Jiangsu, China.
Zhiyong ZhangSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The high-performance low-field magnetic resonance imaging (MRI) system, equipped with modern hardware and contemporary imaging capabilities, has garnered interest within the MRI community in recent years. It has also been proven to have unique advantages over high-field MRI in both physical and cost aspects. However, for susceptibility weighted imaging (SWI), the low signal-to-noise ratio and the long echo time inherent at low field hinder the SWI from being applied to clinical applications. This work optimized the imaging protocol to select suitable parameters such as the values of time of echo (TE), repetition time (TR), and the flip angle (FA) of the RF pulse according to the signal simulations for low-field SWI. To improve the signal-to-noise ratio (SNR) performance, averaging multi-echo magnitude images and BM4D phase denoising were proposed. A comparison of the SWI in 0.5T and 1.5T was carried out, demonstrating the capability to identify magnetic susceptibility differences between variable tissues, especially, the blood veins. This would open the possibility to extend SWI applications in the high-performance low field MRI.

Indexed as

0.5T MRIlow-fieldprotocol optimizationSNR improvementSWI

Identifiers

PMID36312037
PMCPMC9597077

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Registered trials

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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.