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Published in: Insights into Imaging 1/2023

Open Access 01-12-2023 | Original Article

Inter-vendor and inter-observer reliability of diffusion tensor imaging in the musculoskeletal system: a multiscanner MR study

Authors: Vito Chianca, Domenico Albano, Stefania Rizzo, Mario Maas, Luca Maria Sconfienza, Filippo Del Grande

Published in: Insights into Imaging | Issue 1/2023

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Abstract

Background

To evaluate the inter-observer and inter-vendor reliability of diffusion tensor imaging parameters in the musculoskeletal system.

Methods

This prospective study included six healthy volunteers three men (mean age: 42; range: 31–52 years) and three women (mean age: 36; range: 30–44 years).
Each subject was scanned using different 3 Tesla magnetic resonance scanners from three different vendors at three different sites bilaterally. First, the intra-class correlation coefficient was used to determine between-observers agreement for overall measurements and clinical sites. Next, between-group comparisons were made through the nonparametric Friedman’s test. Finally, the Bland–Altman method was used to determine agreement among the three scanner measurements, comparing them two by two.

Results

A total of 792 measurement were calculated. ICC reported high levels of agreement between the two observers. ICC related to MD, FA, and RD measurements ranged from 0.88 (95% CI 0.85–0.90) to 0.95 (95% CI 0.94–0.96), from 0.85 (95% CI 0.81–0.88) to 0.95 (95% CI 0.93–0.96), and from 0.89 (0.85–0.90) to 0.92 (0.90–0.94).
No statistically significant inter-vendor differences were observed. The Bland–Altmann method confirmed a high correlation between parameter values.

Conclusion

An excellent inter-observer and inter-vendor reliability was found in our study.
Appendix
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Metadata
Title
Inter-vendor and inter-observer reliability of diffusion tensor imaging in the musculoskeletal system: a multiscanner MR study
Authors
Vito Chianca
Domenico Albano
Stefania Rizzo
Mario Maas
Luca Maria Sconfienza
Filippo Del Grande
Publication date
01-12-2023
Publisher
Springer Vienna
Published in
Insights into Imaging / Issue 1/2023
Electronic ISSN: 1869-4101
DOI
https://doi.org/10.1186/s13244-023-01374-0

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