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Multi-component T2* relaxation modelling in human Achilles tendon: Quantifying chemical shift information in ultra-short echo time imaging.

Authors :
Anjum, Muhammad A. R.
Gonzalez, Felix M.
Swain, Anshuman
Leisen, Johannes
Hosseini, Zahra
Singer, Adam
Umpierrez, Monica
Reiter, David A.
Source :
Magnetic Resonance in Medicine; Jul2021, Vol. 86 Issue 1, p415-428, 14p
Publication Year :
2021

Abstract

Purpose: To examine multi-component relaxation modelling for quantification of on-and off-resonance relaxation signals in multi-echo ultra-short echo time (UTE) data of human Achilles tendon (AT) and compare bias and dispersion errors of model parameters to that of the bi-component model. Theory and Methods: Multi-component modelling is demonstrated for quantitative multi-echo UTE analysis of AT and supported using a novel method for determining number of MR-visible off-resonance components, UTE data from six healthy volunteers, and analysis of proton NMR measurements from ex vivo bovine AT. Cramer-Rao lower bound expressions are presented for multi-and bi-component models and parameter estimate variances are compared. Bias error in bi-component estimates is characterized numerically. Results: Two off-resonance components were consistently detected in all six volunteers and in bovine AT data. Multi-component model exhibited superior quality of fit, with a marginal increase in estimate variance, when compared to the bi-component model. Bi-component estimates exhibited notable bias particularly in R<subscript>2.1</subscript>* in the presence of off-resonance components. Conclusion: Multi-component modelling more reliably quantifies tendon matrix water components while also providing quantitation of additional non-water matrix constituents. Further work is needed to interpret the origin of the observed offresonance signals with preliminary assignments made to chemical groups in lipids and proteoglycans. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
07403194
Volume :
86
Issue :
1
Database :
Complementary Index
Journal :
Magnetic Resonance in Medicine
Publication Type :
Academic Journal
Accession number :
149994777
Full Text :
https://doi.org/10.1002/mrm.28686