Evidence map›Paper›PMID 38974534›Full record

ArticleSurgical neurology international2024

Applications, limitations and advancements of ultra-low-field magnetic resonance imaging: A scoping review.

Ahmed Altaf, Muhammad Shakir, Hammad Atif Irshad, Shiza Atif, Usha Kumari, Omar Islam, W Taylor Kimberly, Edmond Knopp, Chip Truwit, Khan Siddiqui and 1 more

Abstract readScoping Review
In one paragraph

Article in Surgical neurology international, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Portable Ultra-Low-Field MRI in Outpatient Neurology: An Examination of Clinical Performance and Patient Experience.Journal of neuroimaging : official journal of the American Society of Neuroimaging
    Article
  15. 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

11 authors.

Ahmed AltafDepartment of Surgery, Section of Neurosurgery, Aga Khan University Hospital, Karachi, Sindh, Pakistan.
Muhammad ShakirDepartment of Surgery, Section of Neurosurgery, Aga Khan University Hospital, Karachi, Sindh, Pakistan.
Hammad Atif IrshadMedical College, Aga Khan University Hospital, Karachi, Sindh, Pakistan.
Shiza AtifMedical College, Aga Khan University Hospital, Karachi, Sindh, Pakistan.
Usha KumariMedical College, Peoples University of Medical and Health Sciences for Women, Karachi, Sindh, Pakistan.
Omar IslamDepartment of Diagnostic Radiology, Queen's University, Kingston General Hospital, Kingston, Canada.
W Taylor KimberlyDepartment of Neurology, Massachusetts General Hospital, Boston, United States.
Edmond KnoppHyperfine, Inc., Guilford, United States.
Chip TruwitHyperfine, Inc., Guilford, United States.
Khan SiddiquiHyperfine, Inc., Guilford, United States.
S Ather EnamDepartment of Surgery, Section of Neurosurgery, Aga Khan University Hospital, Karachi, Sindh, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Ultra-low-field magnetic resonance imaging (ULF-MRI) has emerged as an alternative with several portable clinical applications. This review aims to comprehensively explore its applications, potential limitations, technological advancements, and expert recommendations. Methods: A review of the literature was conducted across medical databases to identify relevant studies. Articles on clinical usage of ULF-MRI were included, and data regarding applications, limitations, and advancements were extracted. A total of 25 articles were included for qualitative analysis. Results: The review reveals ULF-MRI efficacy in intensive care settings and intraoperatively. Technological strides are evident through innovative reconstruction techniques and integration with machine learning approaches. Additional advantages include features such as portability, cost-effectiveness, reduced power requirements, and improved patient comfort. However, alongside these strengths, certain limitations of ULF-MRI were identified, including low signal-to-noise ratio, limited resolution and length of scanning sequences, as well as variety and absence of regulatory-approved contrast-enhanced imaging. Recommendations from experts emphasize optimizing imaging quality, including addressing signal-to-noise ratio (SNR) and resolution, decreasing the length of scan time, and expanding point-of-care magnetic resonance imaging availability. Conclusion: This review summarizes the potential of ULF-MRI. The technology's adaptability in intensive care unit settings and its diverse clinical and surgical applications, while accounting for SNR and resolution limitations, highlight its significance, especially in resource-limited settings. Technological advancements, alongside expert recommendations, pave the way for refining and expanding ULF-MRI's utility. However, adequate training is crucial for widespread utilization.

Indexed as

Global healthHealthcare innovationMedical imagingTechnologyUltra-low-field magnetic resonance imaging

Identifiers

PMID38974534
PMCPMC11225429

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

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.