ArticleBMC medical imaging2024
Comparison of different acceleration factors of artificial intelligence-compressed sensing for brachial plexus MRI imaging: scanning time and image quality.
Article in BMC medical imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Brachial Plexopathies: A Comprehensive Radiologic Method Integrating Ultrasound and MRI.Journal of clinical medicine · 2025Review
- Comparing respiratory-triggered T2WI MRI with an artificial intelligence-assisted technique and motion-suppressed respiratory-triggered T2WI in abdominal imaging.Quantitative imaging in medicine and surgery · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background3D brachial plexus MRI scanning is prone to examination failure due to the lengthy scan times, which can lead to patient discomfort and motion artifacts. Our purpose is to investigate the efficacy of artificial intelligence-assisted compressed sensing (ACS) in improving the acceleration efficiency and maintaining or enhancing the image quality of brachial plexus MR imaging.
methodsA total of 30 volunteers underwent 3D sampling perfection with application-optimized contrast using different flip angle evolution short time inversion recovery using a 3.0T MR scanner. The imaging protocol included parallel imaging (PI) and ACS employing acceleration factors of 4.37, 6.22, and 9.03. Radiologists evaluated the neural detail display, fat suppression effectiveness, presence of image artifacts, and overall image quality. Signal intensity and standard deviation of specific anatomical sites within the brachial plexus and background tissues were measured, with signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) subsequently calculated. Cohen's weighted kappa (κ), One-way ANOVA, Kruskal-Wallis and pairwise comparisons with Bonferroni-adjusted significance level. P < 0.05 was considered statistically significant.
resultsACS significantly reduced scanning times compared to PI. Evaluations revealed differences in subjective scores and SNR across the sequences (P < 0.05), with no marked differences in CNR (P > 0.05). For subjective scores, ACS 9.03 were lower than the other three sequences in neural details display, image artifacts and overall image quality. There was no significant difference in fat suppression. For objective quantitative evaluation, SNR of right C6 root in ACS 6.22 and ACS 9.03 was higher than that in PI; SNR of left C6 root in ACS 4.37, ACS 6.22 and ACS 9.03 was higher than that in PI; SNR of medial cord in ACS 6.22, ACS 9.03 was higher than that in PI.
conclusionCompared with PI, ACS can shorten scanning time while ensuring good image quality.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.