Paraspinal back muscles in asymptomatic volunteers: Quantitative and qualitative analysis using computed tomography (CT) and magnetic resonance imaging (MRI)

Background: To evaluate paraspinal back muscles of asymptomatic subjects using qualitative and quantitative analysis on CT and MRI and correlate the results with demographic data. Methods: Twenty-nine asymptomatic subjects were enrolled prospectively (age: mean 34.31, range 23-50; 14 men, 15 women)...

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Main Authors: Choi, I. (Author), Choi, J.-A (Author), Hwang, E. (Author), Khil, E.K (Author), Sidek, S. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd., 2020
Subjects:
MRI
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Summary:Background: To evaluate paraspinal back muscles of asymptomatic subjects using qualitative and quantitative analysis on CT and MRI and correlate the results with demographic data. Methods: Twenty-nine asymptomatic subjects were enrolled prospectively (age: mean 34.31, range 23-50; 14 men, 15 women) from August 2016 to April 2017. Qualitative analysis of muscles was done using Goutallier's system on CT and MRI. Quantitative analysis entailed cross sectional area (CSA) on CT and MRI, Hounsfield unit (HU) on CT, fat fraction using two-point Dixon technique on MRI. Three readers independently analyzed the images; intra- and inter-observer agreements were measured. Linear regression and Spearman's analyses were used for correlation with demographic data. Results: CSA values were significantly higher in men (p < 0.001). Fat fraction was higher (22.53% vs. 14.35%) and HU lower (36.00 vs. 47.43) in women (p < 0.001). Intra- and inter-observer reliabilities of the two methods were greater than 0.8, except for CSA of L5/S1 on MRI; however, regarding quantitative analysis, decreasing HU and increasing fat fraction were correlated with increasing age, female gender and lower lumbar segment (p < 0.001). Conclusion: MRI and CT can be reliably used for qualitative and quantitative analysis of paraspinal back muscles, regarding fat content. Fat fraction and HU showed highest reliabilities. © 2020 The Author(s).
ISBN:14712474 (ISSN)
ISSN:14712474 (ISSN)
DOI:10.1186/s12891-020-03432-w