Evidence map›Paper›PMID 39429612›Full record

ArticleQuantitative imaging in medicine and surgery2024

Accelerating brain three-dimensional T2 fluid-attenuated inversion recovery using artificial intelligence-assisted compressed sensing: a comparison study with parallel imaging.

Jinli Ding, Li Chai, Yunyun Duan, Ziyan Wang, Chengpeng Miao, Shaoxin Xiang, Yuxin Yang, Yaou Liu

Abstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Customizing native T1 mapping: The effects of compressed sensing, deep learning-based denoising, and high-resolution on measurement of native myocardial T1.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
    Article
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

8 authors.

Jinli Ding *Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Li Chai *Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Yunyun DuanDepartment of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Ziyan WangLi Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong, China.
Chengpeng MiaoDepartment of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Shaoxin XiangUnited Imaging Research Institute of Intelligent Imaging, Beijing, China.
Yuxin YangUnited Imaging Research Institute of Intelligent Imaging, Beijing, China.
Yaou LiuDepartment of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Shortening the acquisition time of brain three-dimensional T2 fluid-attenuated inversion recovery (3D T2 FLAIR) by using acceleration techniques has the potential to reduce motion artifacts in images and facilitate clinical application. This study aimed to assess the image quality of brain 3D T2 FLAIR accelerated by artificial intelligence-assisted compressed sensing (ACS) in comparison to 3D T2 FLAIR accelerated by parallel imaging (PI). Methods: In this prospective cohort study, 102 consecutive participants, including both healthy individuals and those with suspected brain diseases, were recruited and underwent both ACS- and PI-3D T2 FLAIR scans with a 3.0-Tesla magnetic resonance imaging system from February 2023 to October 2023 in Beijing Tiantan Hospital, Capital Medical University. Quantitative assessment involved white matter (WM) and gray matter (GM) signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), whole-image sharpness, and tumor volume. Qualitative assessment included the scoring of overall image quality, GM-WM border sharpness, and diagnostic confidence in lesion detection. Results: ACS-3D T2 FLAIR exhibited a shorter acquisition time compared to PI-3D T2 FLAIR (105 Conclusions: The ACS technique offers a substantial reduction in scanning time for brain 3D T2 FLAIR compared to PI while maintaining good image quality and equivalent diagnostic confidence.

Indexed as

artificial intelligence-assisted compressed sensing (AI-ACS)brain magnetic resonance imaging (brain MRI)parallel imaging (PI)T2 fluid-attenuated inversion recovery (T2 FLAIR)

Identifiers

PMID39429612
PMCPMC11485369

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.