Publication
Title
Quantitative STIR of muscle for monitoring nerve regeneration
Author
Abstract
Purpose To assess whether short tau inversion recovery (STIR) MRI sequences can provide a tool for monitoring peripheral nerve regeneration, by comparing signal intensity changes in reinnervated muscle over time, and to determine potential clinical time points for monitoring. Materials and Methods For this prospective study, 29 patients with complete traumatic transection of the ulnar or median nerves in the forearm were followed up to 45 months postsurgery. Standardized 1.5 Tesla STIR-MRI scans of hand muscles were obtained at fixed time intervals. Muscle signal intensities were measured semi-quantitatively and correlated to functional outcome. Results For the patients with good function recovery, mean signal intensity ratios of 1.179 ± 0.039, 1.304 ± 0.180, 1.154 ± 0.121, 1.105 ± 0.046 and 1.038 ± 0.047 were found at 1-, 3-, 6-, 9-, and 12-month follow-up, respectively. In the group with poor function recovery, ratios of 1.240 ± 0.069, 1.374 ± 0.144, 1.407 ± 0.127, 1.386 ± 0.128 and 1.316 ± 0.116 were found. Comparing the groups showed significant differences from 6 months onward (P < 0.001), with normalizing signal intensities in the group with good function recovery and sustained elevated signal intensity in the group with poor function recovery. Conclusion MRI of muscle can be used as a tool for monitoring motor nerve regeneration, by comparing STIR muscle signal intensities over time. A decrease in signal intensity ratio of 50% (as compared to the initial increase) seems to predict good function recovery. Long-term follow-up shows that STIR MRI can be used for at least 15 months after nerve transection to differentiate between denervated and (re)innervated muscles.
Language
English
Source (journal)
Journal of magnetic resonance imaging. - Chicago, Ill.
Publication
Chicago, Ill. : 2016
ISSN
1053-1807
Volume/pages
44:2(2016), p. 401-410
ISI
000380068100016
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
Faculty/Department
Research group
[E?say:metaLocaldata.cgzprojectinf]
Publication type
Subject
External links
Web of Science
Record
Identification
Creation 28.04.2016
Last edited 14.11.2017
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