AI Article Synopsis

  • 3D brachial plexus MRI scanning often faces issues like long scan times that can cause patient discomfort and image quality problems due to motion artifacts.
  • The study tested artificial intelligence-assisted compressed sensing (ACS) for enhancing MRI efficiency and image quality using a 3.0T MR scanner on 30 volunteers.
  • Results showed that ACS reduced scan times significantly compared to standard methods, but subjective image quality scores varied, with some sequences performing worse in terms of neural detail and artifacts, while signal-to-noise ratios improved with ACS use.

Article Abstract

Background: 3D 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.

Methods: A 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.

Results: ACS 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.

Conclusion: Compared with PI, ACS can shorten scanning time while ensuring good image quality.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11566112PMC
http://dx.doi.org/10.1186/s12880-024-01493-0DOI Listing

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