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. 59 121-129

Subject Categories

Medical Equipment Engineering

Radiology, Nuclear Medicine and Medical Imaging

Medical Image Processing

DOI

10.1016/j.mri.2019.03.008

More information

Latest update

10/11/2022