Reproducibility and repeatability of MRI-based body composition analysis

Magn Reson Med. 2020 Dec;84(6):3146-3156. doi: 10.1002/mrm.28360. Epub 2020 Jun 10.

Abstract

Purpose: There is an absence of reproducibility studies on MRI-based body composition analysis in current literature. Therefore, the aim of this study was to investigate the between-scanner reproducibility and the repeatability of a method for MRI-based body composition analysis.

Methods: Eighteen healthy volunteers of varying body mass index and adiposity were each scanned twice on five different 1.5T and 3T scanners from three different vendors. Two-point Dixon neck-to knee images and two additional liver scans were acquired with similar protocols. Visceral adipose tissue (VAT) volume, abdominal subcutaneous adipose tissue (ASAT) volume, thigh muscle volume, and muscle fat infiltration (MFI) in the thigh muscle were measured. Liver proton density fat fraction (PDFF) was assessed using two different methods, the scanner vendor's 6-point method and an in-house 2-point method. Within-scanner test-retest repeatability and between-scanner reproducibility were calculated using analysis of variance.

Results: Repeatability coefficients were 13 centiliters (cl) (VAT), 24 cl (ASAT), 17 cl (total thigh muscle volume), 0.53% (MFI), and 1.27-1.37% for liver PDFF. Reproducibility coefficients were 24 cl (VAT), 42 cl (ASAT), 31 cl (total thigh muscle volume), 1.44% (MFI), and 2.37-2.40% for liver PDFF.

Conclusion: For all measures except MFI, the within-scanner repeatability explained much of the overall reproducibility. The two methods for measuring liver fat had similar reproducibility. This study showed that the investigated method eliminates effects due to scanner differences. The results can be used for power calculations in clinical studies or to better understand the scanner-induced variability in clinical applications.

Keywords: MRI; body composition analysis; chemical shift encoded MRI; fat fraction; repeatability; reproducibility; water-fat imaging.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adipose Tissue / diagnostic imaging
  • Body Composition*
  • Humans
  • Liver
  • Magnetic Resonance Imaging*
  • Reproducibility of Results