Analysis of the effect of motion on highly accelerated 3D FatNavs in 3D brain images acquired at 3T
Elisa Marchetto, Daniel Gallichan
Abstract
3D FatNavs are rapid acquisitions of MRI fat-volumes within the head that can be used for retrospective motion correction for brain MRI. 3D FatNavs typically use very high acceleration factors and are reconstructed with the GRAPPA parallel imaging technique.
Introduction
A retrospective motion correction technique for brain MR images has been proposed by Gallichan et al. [1] to detect and correct non-deliberate motion during high-resolution imaging. The idea consists of applying a 3D GRE sequence combined with a three-pulse fat-selective binomial excitation as a navigator.
Materials and Methods
Five different datasets of MPRAGE brain MR images were acquired on a Prisma scanner (Siemens Healthcare, Erlangen, Germany) at 1 mm isotropic resolution, with TI/TE/TR = 1100/3.03/2410 ms, FA = 8° and R = 2, using a 64-channel head coil with a total scanning time of 5:38 min.
Result
Fig 5 compares 3D FatNav volumes before and after the GRAPPA "re-reconstruction" step for four different levels of motion (low, medium, high and very high) randomly selected from the 225 different combinations of motion parameters applied to the acquired 3D FatNav volumes.
Discussion
In this study, we assessed a simulation of the accuracy of motion parameter estimation from 3D FatNavs across a broad range of head motion. GRAPPA reconstruction of the 3D FatNav volumes was expected to perform poorly in the case of large head position changes.
Conclusions
In this study, data from five MPRAGE brain images acquired at 3T were used to estimate the motion corresponding to four image quality boundaries and assess motion tolerance when 3D FatNav-based motion correction is used.
Citation: Marchetto E, Gallichan D (2024) Analysis of the effect of motion on highly accelerated 3D FatNavs in 3D brain images acquired at 3T. PLoS ONE 19(7): e0306078. https://doi.org/10.1371/journal.pone.0306078
Editor: Federico Giove, Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi, ITALY
Received: December 15, 2023; Accepted: June 11, 2024; Published: July 25, 2024
Copyright: © 2024 Marchetto, Gallichan. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The data used in this study contains potentially sensitive information, as the data is Structural MR data which is highly confidential personal data (even de-faced). The data and scripts that support the findings of this study are available upon reasonable request. These restrictions are imposed by Cardiff University Brain Research Imaging Centre (CUBRIC) data sharing policy, under which the data have been acquired, and by Cardiff University School of Psychology Ethics Committee board which approved this study (in April 2020 - EC.20.04.14.6009G). The policy is based on the UK General Data Protection Regulation (GDPR) introduced in the 2018. Access to the data necessary to replicate the findings of this study can be requested to the correspondent author at elisa.marchetto@nyulangone.org or to the CUBRIC Data Team at cubricit@cardiff.ac.uk. For more information or inquiry about CUBRIC policies please contact CUBRIC Compute and Data department: cubricit@cardiff.ac.uk. Cardiff University sharing policy can be found here: https://www.cardiff.ac.uk/public-information/policies-and-procedures/data-protection.
Funding: The authors received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Source: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0306078#abstract0
