Repeatability and reproducibility of longitudinal relaxation rate in 12 small-animal MRI systems
Journal article, 2019
Background: Many translational MR biomarkers derive from measurements of the water proton longitudinal relaxation rate R 1 , but evidence for between-site reproducibility of R 1 in small-animal MRI is lacking. Objective: To assess R 1 repeatability and multi-site reproducibility in phantoms for preclinical MRI. Methods: R 1 was measured by saturation recovery in 2% agarose phantoms with five nickel chloride concentrations in 12 magnets at 5 field strengths in 11 centres on two different occasions within 1–13 days. R 1 was analysed in three different regions of interest, giving 360 measurements in total. Root-mean-square repeatability and reproducibility coefficients of variation (CoV) were calculated. Propagation of reproducibility errors into 21 translational MR measurements and biomarkers was estimated. Relaxivities were calculated. Dynamic signal stability was also measured. Results: CoV for day-to-day repeatability (N = 180 regions of interest) was 2.34% and for between-centre reproducibility (N = 9 centres) was 1.43%. Mostly, these do not propagate to biologically significant between-centre error, although a few R 1 -based MR biomarkers were found to be quite sensitive even to such small errors in R 1 , notably in myocardial fibrosis, in white matter, and in oxygen-enhanced MRI. The relaxivity of aqueous Ni 2+ in 2% agarose varied between 0.66 s −1 mM −1 at 3 T and 0.94 s −1 mM −1 at 11.7T. Interpretation: While several factors affect the reproducibility of R 1 -based MR biomarkers measured preclinically, between-centre propagation of errors arising from intrinsic equipment irreproducibility should in most cases be small. However, in a few specific cases exceptional efforts might be required to ensure R 1 -reproducibility.
Phantom
Relaxation time
Reproducibility
Biomarker
MRI
Hardware stability
Error propagation
Author
John C. Waterton
University of Manchester
Bioxydyn Limited
Catherine D.G. Hines
Merck & Co., Inc.
Paul Hockings
MedTech West
Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering
Iina Laitinen
Sanofi-Aventis Deutschland GmbH
Sabina Ziemian
Bayer AG
Simon Campbell
GlaxoSmithKline
Michael Gottschalk
Lund University
Claudia Green
Bayer AG
Michael Haase
GlaxoSmithKline
Katja Hassemer
Sanofi-Aventis Deutschland GmbH
Hans Paul Juretschke
Sanofi-Aventis Deutschland GmbH
Sascha Koehler
Bruker BioSpin GmbH, Germany
William Lloyd
University of Manchester
Yanping Luo
AbbVie
Irma Mahmutovic Persson
Lund University
James P.B. O'Connor
University of Manchester
Lars E Olsson
Lund University
Kashmira Pindoria
GlaxoSmithKline
Jurgen E. Schneider
University of Leeds
Steven Sourbron
University of Leeds
Denise Steinmann
Sanofi-Aventis Deutschland GmbH
Klaus Strobel
Bruker BioSpin GmbH, Germany
Sirisha Tadimalla
University of Leeds
Irvin Teh
University of Leeds
Andor Veltien
Radboud University
Xiaomeng Zhang
AbbVie
Gunnar Schütz
Bayer AG
Magnetic Resonance Imaging
0730-725X (ISSN) 18735894 (eISSN)
Vol. 59 121-129Subject Categories
Medical Equipment Engineering
Radiology, Nuclear Medicine and Medical Imaging
Medical Image Processing
DOI
10.1016/j.mri.2019.03.008