Multi‐component T2∗ relaxation modelling in human Achilles tendon: Quantifying chemical shift information in ultra‐short echo time imaging. Issue 1 (15th February 2021)

• Record Type: Journal Article
• Authors: Anjum, Muhammad A. R.; Gonzalez, Felix M.; Swain, Anshuman; Leisen, Johannes; Hosseini, Zahra; Singer, Adam; Umpierrez, Monica; Reiter, David A.
• Is Part Of: Magnetic resonance in medicine. Volume 86:Issue 1(2021)
• Page Start: 415
• Page End: 428
• Publication Date: 2021-02-15
• Subjects: Cramer Rao lower bound -- multi‐echo UTE -- Multi‐exponential -- quantitative MRI -- tendinopathy -- ultrashort echo time; Nuclear magnetic resonance -- Periodicals; Electron paramagnetic resonance -- Periodicals; 616.07548
• DOI: 10.1002/mrm.28686
• Languages: English
• ISSNs: 0740-3194

Abstract

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 2, 1 ∗ 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 off‐resonance signals with preliminary assignments made to chemical groups in lipids and proteoglycans.