Synergistic motion compensation strategies for positron emission tomography when acquired simultaneously with magnetic resonance imaging

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Abstract

Subject motion in positron emission tomography (PET) is a key factor that degrades image resolution and quality, limiting its potential capabilities. Correcting for it is complicated due to the lack of sufficient measured PET data from each position. This poses a significant barrier in calculating the amount of motion occurring during a scan. Motion correction can be implemented at different stages of data processing either during or after image reconstruction, and once applied accurately can substantially improve image quality and information accuracy. With the development of integrated PET-MRI (magnetic resonance imaging) scanners, internal organ motion can be measured concurrently with both PET and MRI. In this review paper, we explore the synergistic use of PET and MRI data to correct for any motion that affects the PET images. Different types of motion that can occur during PET-MRI acquisitions are presented and the associated motion detection, estimation and correction methods are reviewed. Finally, some highlights from recent literature in selected human and animal imaging applications are presented and the importance of motion correction for accurate kinetic modelling in dynamic PET-MRI is emphasized.

This article is part of the theme issue ‘Synergistic tomographic image reconstruction: part 2’.

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Most cited references 109

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Motion correction with PROPELLER MRI: application to head motion and free-breathing cardiac imaging.

James Pipe (1999)

A method for motion correction, involving both data collection and reconstruction, is presented. The PROPELLER MRI method collects data in concentric rectangular strips rotated about the k-space origin. The central region of k-space is sampled for every strip, which (a) allows one to correct spatial inconsistencies in position, rotation, and phase between strips, (b) allows one to reject data based on a correlation measure indicating through-plane motion, and (c) further decreases motion artifacts through an averaging effect for low spatial frequencies. Results are shown in which PROPELLER MRI is used to correct for bulk motion in head images and respiratory motion in nongated cardiac images. Magn Reson Med 42:963-969, 1999. Copyright 1999 Wiley-Liss, Inc.

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PROMO: Real-time prospective motion correction in MRI using image-based tracking.

J. Cooper Roddey, Imelda J. Santos, Dan Rettmann … (2009)

Artifacts caused by patient motion during scanning remain a serious problem in most MRI applications. The prospective motion correction technique attempts to address this problem at its source by keeping the measurement coordinate system fixed with respect to the patient throughout the entire scan process. In this study, a new image-based approach for prospective motion correction is described, which utilizes three orthogonal two-dimensional spiral navigator acquisitions, along with a flexible image-based tracking method based on the extended Kalman filter algorithm for online motion measurement. The spiral navigator/extended Kalman filter framework offers the advantages of image-domain tracking within patient-specific regions-of-interest and reduced sensitivity to off-resonance-induced corruption of rigid-body motion estimates. The performance of the method was tested using offline computer simulations and online in vivo head motion experiments. In vivo validation results covering a broad range of staged head motions indicate a steady-state error of less than 10% of the motion magnitude, even for large compound motions that included rotations over 15 deg. A preliminary in vivo application in three-dimensional inversion recovery spoiled gradient echo (IR-SPGR) and three-dimensional fast spin echo (FSE) sequences demonstrates the effectiveness of the spiral navigator/extended Kalman filter framework for correcting three-dimensional rigid-body head motion artifacts prospectively in high-resolution three-dimensional MRI scans. Copyright (c) 2009 Wiley-Liss, Inc.

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Respiratory motion models: a review.

J McClelland, D Hawkes, T Schaeffter … (2013)

The problem of respiratory motion has proved a serious obstacle in developing techniques to acquire images or guide interventions in abdominal and thoracic organs. Motion models offer a possible solution to these problems, and as a result the field of respiratory motion modelling has become an active one over the past 15 years. A motion model can be defined as a process that takes some surrogate data as input and produces a motion estimate as output. Many techniques have been proposed in the literature, differing in the data used to form the models, the type of model employed, how this model is computed, the type of surrogate data used as input to the model in order to make motion estimates and what form this output should take. In addition, a wide range of different application areas have been proposed. In this paper we summarise the state of the art in this important field and in the process highlight the key papers that have driven its advance. The intention is that this will serve as a timely review and comparison of the different techniques proposed to date and as a basis to inform future research in this area.

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Contributors

Charalampos Tsoumpas:

ORCID: http://orcid.org/0000-0002-4971-2477

Journal

Journal ID (nlm-ta): Philos Trans A Math Phys Eng Sci

Journal ID (iso-abbrev): Philos Trans A Math Phys Eng Sci

Journal ID (publisher-id): RSTA

Journal ID (hwp): roypta

Title: Philosophical transactions. Series A, Mathematical, physical, and engineering sciences

Publisher: The Royal Society Publishing

ISSN (Print): 1364-503X

ISSN (Electronic): 1471-2962

Publication date (Print, pub): August 23, 2021

Publication date (Electronic, pub): July 5, 2021

Publication date PMC-release: July 5, 2021

Volume: 379

Issue: 2204 , Theme issue ‘Synergistic tomographic image reconstruction: part 2’ compiled and edited by Charalampos Tsoumpas, Jakob Sauer Jørgensen, Christoph Kolbitsch and Kris Thielemans

Electronic Location Identifier: 20200207

Affiliations

[ ¹ ] Department of Health Sciences, European University of Cyprus, , Nicosia, Cyprus

[ ² ] Biomedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, , New York, NY, USA

[ ³ ] Biomedical Imaging Science Department, University of Leeds, , West Yorkshire, UK

[ ⁴ ] Invicro, , London, UK

Author notes

One contribution of 9 to a theme issue ‘ Synergistic tomographic image reconstruction: part 2’.

Author information

Irene Polycarpou http://orcid.org/0000-0003-3109-2983

Georgios Soultanidis http://orcid.org/0000-0001-9620-1728

Charalampos Tsoumpas http://orcid.org/0000-0002-4971-2477

Article

Publisher ID: rsta20200207

DOI: 10.1098/rsta.2020.0207

PMC ID: 8255946

PubMed ID: 34218675

SO-VID: f81be7ec-7741-42fa-a6c2-1ecdbcf48ff0

License:

Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

History

Date accepted : April 15, 2021

Funding

Funded by: Engineering and Physical Sciences Research Council, http://dx.doi.org/10.13039/501100000266;

Award ID: EP/P022200/1

Award ID: EP/T026693/1

Funded by: Royal Society, http://dx.doi.org/10.13039/501100000288;

Award ID: IF170011

Custom metadata

cover-date August 23, 2021

Keywords: positron emission tomography and magnetic resonance imaging,motion correction,resolution

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Keywords: positron emission tomography and magnetic resonance imaging, motion correction, resolution

Synergistic motion compensation strategies for positron emission tomography when acquired simultaneously with magnetic resonance imaging

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Abstract

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Electron Channelling Contrast Imaging (ECCI)

Most cited references 109

Motion correction with PROPELLER MRI: application to head motion and free-breathing cardiac imaging.

PROMO: Real-time prospective motion correction in MRI using image-based tracking.

Respiratory motion models: a review.

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Affiliations

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