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Three dimensional MRF obtains highly repeatable and reproducible multi-parametric estimations in the healthy human brain at 1.5T and 3T

Authors :
Guido Buonincontri
Jan W. Kurzawski
Joshua D Kaggie
Tomasz Matys
Ferdia A Gallagher
Matteo Cencini
Graziella Donatelli
Paolo Cecchi
Mirco Cosottini
Nicola Martini
Francesca Frijia
Domenico Montanaro
Pedro A. Gómez
Rolf F Schulte
Alessandra Retico
Michela Tosetti
Source :
NeuroImage, Vol 226, Iss , Pp 117573- (2021)
Publication Year :
2021
Publisher :
Elsevier, 2021.

Abstract

Magnetic resonance fingerprinting (MRF) is highly promising as a quantitative MRI technique due to its accuracy, robustness, and efficiency. Previous studies have found high repeatability and reproducibility of 2D MRF acquisitions in the brain. Here, we have extended our investigations to 3D MRF acquisitions covering the whole brain using spiral projection k-space trajectories.Our travelling head study acquired test/retest data from the brains of 12 healthy volunteers and 8 MRI systems (3 systems at 3 T and 5 at 1.5 T, all from a single vendor), using a study design not requiring all subjects to be scanned at all sites. The pulse sequence and reconstruction algorithm were the same for all acquisitions.After registration of the MRF-derived PD T1 and T2 maps to an anatomical atlas, coefficients of variation (CVs) were computed to assess test/retest repeatability and inter-site reproducibility in each voxel, while a General Linear Model (GLM) was used to determine the voxel-wise variability between all confounders, which included test/retest, subject, field strength and site.Our analysis demonstrated a high repeatability (CVs 0.7–1.3% for T1, 2.0–7.8% for T2, 1.4–2.5% for normalized PD) and reproducibility (CVs of 2.0–5.8% for T1, 7.4–10.2% for T2, 5.2–9.2% for normalized PD) in gray and white matter.Both repeatability and reproducibility improved when compared to similar experiments using 2D acquisitions. Three-dimensional MRF obtains highly repeatable and reproducible estimations of T1 and T2, supporting the translation of MRF-based fast quantitative imaging into clinical applications.

Details

Language :
English
ISSN :
10959572
Volume :
226
Issue :
117573-
Database :
Directory of Open Access Journals
Journal :
NeuroImage
Publication Type :
Academic Journal
Accession number :
edsdoj.5b2f15a0a27c4d67b3c0afaadd196fff
Document Type :
article
Full Text :
https://doi.org/10.1016/j.neuroimage.2020.117573