Accurate fatty acid composition estimation of adipose tissue in the abdomen based on bipolar multi-echo MRI.

Journal Article (Journal Article)

PURPOSE: To develop a bipolar multi-echo MRI method for the accurate estimation of the adipose tissue fatty acid composition (FAC) using clinically relevant protocols at clinical field strength. METHODS: The proposed technique jointly estimates confounding factors (field map, R 2 * , eddy-current phase) and triglyceride saturation state parameters by fitting multi-echo gradient echo acquisitions to a complex signal model. The noise propagation behavior was improved by applying a low-rank enforcing denoising technique and by addressing eddy-current-induced phase discrepancies analytically. The impact of the total echo train duration on the FAC parameter map accuracy was analyzed in an oil phantom at 3T. Accuracy and reproducibility assessment was based on in vitro oil phantom measurements at two field strengths (3T and 1.5T) and with two different protocols. Repeatability was assessed in vivo in patients (n = 8) with suspected fatty liver disease using test-retest acquisitions in the abdominal subcutaneous, perirenal and mesenteric fat depots. RESULTS: Echo train readout durations of at least five times the conventional in-phase time were required for accurate FAC estimation in areas of high fat content. In vitro, linear regression and Bland-Altman analyses demonstrated strong (r > 0.94) and significant (P ≪ 0.01) correlations between measured and reference FACs for all acquisitions, with smaller overall intercepts and biases at 3T compared to 1.5T. In vivo, reported mean absolute differences between test and retest were 1.54%, 3.31%, and 2.63% for the saturated, mono-unsaturated, and poly-unsaturated fat component, respectively. CONCLUSIONS: Accurate and reproducible MRI-based FAC quantification within a breath-hold is possible at clinical field strengths.

Full Text

Duke Authors

Cited Authors

  • Schneider, M; Janas, G; Lugauer, F; Hoppe, E; Nickel, D; Dale, BM; Kiefer, B; Maier, A; Bashir, MR

Published Date

  • April 2019

Published In

Volume / Issue

  • 81 / 4

Start / End Page

  • 2330 - 2346

PubMed ID

  • 30368904

Electronic International Standard Serial Number (EISSN)

  • 1522-2594

Digital Object Identifier (DOI)

  • 10.1002/mrm.27557


  • eng

Conference Location

  • United States