Rationale and Objectives
To assess the potential of 0.55T low-field MRI system in lumbar spine imaging with
and without the use of additional advanced postprocessing techniques.
Materials and Methods
The lumbar spine of 14 volunteers (32.9 ± 3.6 years) was imaged both at 0.55T and
1.5T using sequences from clinical routine. On the 0.55T scanner system, additional
sequences with simultaneous multi-slice acquisition and artificial intelligence-based
postprocessing techniques were acquired. Image quality of all 28 examinations was
assessed by three musculoskeletal radiologists with respect to signal/contrast, resolution,
and assessability of the spinal canal and neuroforamina using a 5-point Likert scale
(1 = non-diagnostic to 5 = perfect quality). Interrater agreement was evaluated with
the Intraclass Correlation Coefficient and the Mann-Whitney U test (significance level:
p < 0.05).
Results
Image quality at 0.55T was rated lower on the 5-point Likert scale compared to 1.5T
regarding signal/contrast (mean: 4.16 ± 0.29 vs. 4.54 ± 0.29; p < 0.001), resolution (4.07 ± 0.31 vs. 4.49 ± 0.30; p < 0.001), assessability of the spinal canal (4.28 ± 0.13 vs. 4.73 ± 0.26; p < 0.001) and the neuroforamina (4.14 ± 0.28 vs. 4.70 ± 0.27; p < 0.001). Image quality for the AI-processed sagittal T1 TSE and T2 TSE at 0.55T
was also rated slightly lower, but still good to perfect with a concomitant reduction
in measurement time. Interrater agreement was good to excellent (range: 0.60–0.91).
Conclusion
While lumbar spine image quality at 0.55T is perceived inferior to imaging at 1.5T
by musculoskeletal radiologists, good overall examination quality was observed with
high interrater agreement. Advanced postprocessing techniques may accelerate intrinsically
longer acquisition times at 0.55T.
Key Words
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Article info
Publication history
Published online: February 23, 2023
Accepted:
January 29,
2023
Received in revised form:
January 29,
2023
Received:
October 13,
2022
Publication stage
In Press Corrected ProofIdentification
Copyright
© 2023 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
