Literature DB >> 26117701

Collapsed fat navigators for brain 3D rigid body motion.

Mathias Engström1, Magnus Mårtensson2, Enrico Avventi2, Ola Norbeck2, Stefan Skare2.   

Abstract

PURPOSE: To acquire high-resolution 3D multi-slab echo planar imaging data without motion artifacts, using collapsed fat navigators.
METHODS: A fat navigator module (collapsed FatNav) was added to a diffusion-weighted 3D multi-slab echo planar imaging (DW 3D-MS EPI) sequence, comprising three orthogonal echo planar imaging readouts to track rigid body head motion in the image domain and performing prospective motion correction. The stability, resolution and accuracy of the navigator were investigated on phantoms and healthy volunteers.
RESULTS: The experiments on phantoms and volunteers show that the navigator, depicting projections of the subcutaneous fat in of the head, is capable of correcting for head motion with insignificant bias compared to motion estimates derived from the water-signaling DWI images. Despite that this projection technique implies a non-sparse image appearance, collapsed FatNav data could be highly accelerated with parallel imaging, allowing three orthogonal 2D EPI readouts in about 6ms.
CONCLUSION: By utilizing signal from the leading fat saturation RF pulse of the diffusion sequence, only the readout portion of the navigator needs to be added, resulting in a scan time penalty of only about 5%. Motion can be detected and corrected for with a 5-10Hz update frequency when combined with a sequence like the DW 3D-MS EPI.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Chemical saturation; Fat navigator; Motion correction; Prospective correction

Mesh:

Year:  2015        PMID: 26117701     DOI: 10.1016/j.mri.2015.06.014

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  12 in total

1.  Evaluation of 3D fat-navigator based retrospective motion correction in the clinical setting of patients with brain tumors.

Authors:  Carl Glessgen; Daniel Gallichan; Manuela Moor; Nicolin Hainc; Christian Federau
Journal:  Neuroradiology       Date:  2019-01-23       Impact factor: 2.804

Review 2.  From simultaneous to synergistic MR-PET brain imaging: A review of hybrid MR-PET imaging methodologies.

Authors:  Zhaolin Chen; Sharna D Jamadar; Shenpeng Li; Francesco Sforazzini; Jakub Baran; Nicholas Ferris; Nadim Jon Shah; Gary F Egan
Journal:  Hum Brain Mapp       Date:  2018-08-04       Impact factor: 5.038

3.  A within-coil optical prospective motion-correction system for brain imaging at 7T.

Authors:  Phillip DiGiacomo; Julian Maclaren; Murat Aksoy; Elizabeth Tong; Mackenzie Carlson; Bryan Lanzman; Syed Hashmi; Ronald Watkins; Jarrett Rosenberg; Brian Burns; Timothy W Skloss; Dan Rettmann; Brian Rutt; Roland Bammer; Michael Zeineh
Journal:  Magn Reson Med       Date:  2020-02-20       Impact factor: 4.668

4.  Fat navigators and Moiré phase tracking comparison for motion estimation and retrospective correction.

Authors:  Frédéric Gretsch; Hendrik Mattern; Daniel Gallichan; Oliver Speck
Journal:  Magn Reson Med       Date:  2019-08-09       Impact factor: 4.668

5.  Toward "plug and play" prospective motion correction for MRI by combining observations of the time varying gradient and static vector fields.

Authors:  Adam van Niekerk; Andre van der Kouwe; Ernesta Meintjes
Journal:  Magn Reson Med       Date:  2019-05-07       Impact factor: 4.668

Review 6.  High-resolution Structural Magnetic Resonance Imaging and Quantitative Susceptibility Mapping.

Authors:  Vivek Yedavalli; Phillip DiGiacomo; Elizabeth Tong; Michael Zeineh
Journal:  Magn Reson Imaging Clin N Am       Date:  2021-02       Impact factor: 2.266

7.  Prospective motion correction improves the sensitivity of fMRI pattern decoding.

Authors:  Pei Huang; Johan D Carlin; Arjen Alink; Nikolaus Kriegeskorte; Richard N Henson; Marta M Correia
Journal:  Hum Brain Mapp       Date:  2018-06-08       Impact factor: 5.038

8.  Improvement in diagnostic quality of structural and angiographic MRI of the brain using motion correction with interleaved, volumetric navigators.

Authors:  Mads Andersen; Isabella M Björkman-Burtscher; Anouk Marsman; Esben Thade Petersen; Vincent Oltman Boer
Journal:  PLoS One       Date:  2019-05-17       Impact factor: 3.240

9.  Motion correction methods for MRS: experts' consensus recommendations.

Authors:  Ovidiu C Andronesi; Pallab K Bhattacharyya; Wolfgang Bogner; In-Young Choi; Aaron T Hess; Phil Lee; Ernesta M Meintjes; M Dylan Tisdall; Maxim Zaitzev; André van der Kouwe
Journal:  NMR Biomed       Date:  2020-07-20       Impact factor: 4.044

10.  Improved motion correction of submillimetre 7T fMRI time series with Boundary-Based Registration (BBR).

Authors:  Pei Huang; Johan D Carlin; Richard N Henson; Marta M Correia
Journal:  Neuroimage       Date:  2020-01-18       Impact factor: 6.556

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