Motion Correction in MR

Correction of Position, Motion, and Dynamic Field Changes

1st Edition, Volume 6 - October 26, 2022
Imprint: Academic Press
Editors: Andre van der Kouwe, Jalal B. Andre
Language: English
Paperback ISBN:
9 7 8 - 0 - 1 2 - 8 2 4 4 6 0 - 9
eBook ISBN:
9 7 8 - 0 - 1 2 - 8 2 4 4 7 8 - 4

Motion Correction in MR: Correction of Position, Motion, and Dynamic Changes, Volume Eight provides a comprehensive survey of the state-of-the-art in motion detection and correctio… Read more

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Motion Correction in MR: Correction of Position, Motion, and Dynamic Changes, Volume Eight provides a comprehensive survey of the state-of-the-art in motion detection and correction in magnetic resonance imaging and magnetic resonance spectroscopy. The book describes the problem of correctly and consistently identifying and positioning the organ of interest and tracking it throughout the scan. The basic principles of how image artefacts arise because of position changes during scanning are described, along with retrospective and prospective techniques for eliminating these artefacts, including classical approaches and methods using machine learning.

Internal navigator-based approaches as well as external systems for estimating motion are also presented, along with practical applications in each organ system and each MR modality covered. This book provides a technical basis for physicists and engineers to develop motion correction methods, giving guidance to technologists and radiologists for incorporating these methods in patient examinations.

Cover
Title page
Table of Contents
Copyright
List of contributors
Preface
Part 1: Motion in MR scans
Chapter 1: Why do patients move?
Abstract
1.1: Introduction
1.2: Types of motion
1.3: How motion affects MR acquisition
1.4: Why do patients move?
1.5: Cost of motion
1.6: Motion-mitigating solutions
1.7: Conclusion
Acknowledgments
References
Chapter 2: Impact of motion on research studies
Abstract
2.1: Why is motion a problem for research imaging studies?
2.2: Motion in structural research imaging
2.3: Motion in single-shot EPI for functional MRI
2.4: Motion in single-shot EPI for DWI
2.5: Summary
Acknowledgments
References
Chapter 3: Cost economy of motion
Abstract
3.1: Introduction
3.2: What affects costs in MR?
3.3: Frequency of undesired patient motion
3.4: Financial impact
3.5: Conclusion
References
Chapter 4: Physical and pharmacologic solutions
Abstract
4.1: Introduction
4.2: Physical solution
4.3: Intravenous induction medications
4.4: Most commonly used medications for minimal and moderate sedation
4.5: Medications used to produce deep sedation and general anesthesia
4.6: Other medications used in monitored anesthesia care or general anesthesia by class
4.7: Special consideration for pediatric patients
4.8: Challenges for the anesthesiologist in the magnetic resonance imaging suite
4.9: Hospital/payer costs for nonoperating room anesthesia
References
Chapter 5: Psychosocial solutions
Abstract
5.1: Introduction
5.2: The patient experience
5.3: Psychological interventions to reduce anxiety and motion in MRI
5.4: Step by step interventional guide for radiologists and radiology technologists
5.5: Conclusion
References
Part 2: Consistent anatomical selection
Chapter 6: Automatically detecting anatomy: Robust multiscale anatomy alignment for magnetic resonance imaging
Abstract
6.1: Introduction
6.2: Background and related work
6.3: Proposed method
6.4: Experiments and results
6.5: Conclusions
Disclaimer
References
Chapter 7: Anatomical coordinate systems in brain analysis
Abstract
7.1: Introduction
7.2: Coordinate systems—From empiricism to theory
7.3: The Talairach coordinate system and other atlas-based approaches for lesion analysis in neurology and neuropsychology
7.4: Cortex-based coordinate systems
7.5: White matter organization
7.6: Scanner implementations
7.7: Scanner coordinate systems and image labeling
7.8: Clinical relevance of coordinate systems
7.9: Conclusion
Acknowledgments
References
Part 3: Scan quality and motion metrics
Chapter 8: Metrics for motion and MR quality assessment
Abstract
8.1: Introduction
8.2: Quality assessment strategies
8.3: Describing motion
8.4: Describing the quality of motion measurements
8.5: Describing quality of images
8.6: Conclusions and future directions
References
Chapter 9: Digital and physical phantoms for motion and flow simulation
Abstract
9.1: Introduction
9.2: Motion simulation purposes
9.3: Motion simulation challenges
9.4: Digital phantoms for motion simulation
9.5: Physical phantoms for motion simulation
9.6: Motion simulation phantoms summary
References
Chapter 10: Operational analytics using modality log files
Abstract
10.1: Introduction
10.2: Modality log files
10.3: Imaging workflow analytics
10.4: Conclusions and outlook
References
Part 4: Dynamic effects that compromise scan quality in MRI
Chapter 11: Types of motion
Abstract
11.1: Introduction
11.2: Brief review of MR physics
11.3: Defining and characterizing motion and motion artifacts
11.4: Special considerations, an organ-based approach
11.5: Conclusion
References
Chapter 12: Other dynamic changes
Abstract
12.1: Initial scanner adjustments
12.2: Subsequent changes caused by physiology
12.3: Changes in B0
12.4: B1 changes associated with motion
References
Part 5: Methods of detecting motion and associated field changes in real time
Chapter 13: External tracking systems
Abstract
13.1: General concepts
13.2: Types of external tracking system
13.3: Future directions
References
Chapter 14: k-Space navigators
Abstract
14.1: Introduction
14.2: Rigid-body motion in k-space
14.3: Specific navigator designs
14.4: Summary
References
Chapter 15: Image-space navigators
Abstract
15.1: Introduction
15.2: 1D navigators
15.3: 2D navigators
15.4: 2D/3D “hybrid” navigators
15.5: 3D navigators
15.6: Self-navigation
15.7: Nonwater navigators
15.8: Image-based navigator considerations
15.9: Pros and cons of image-based approaches
15.10: Summary
References
Chapter 16: Navigators without gradients
Abstract
16.1: Introduction
16.2: Motion detection with FID navigators
16.3: Motion measurement with FID navigators
16.4: B0 field measurement with FID navigators
16.5: Discussion
16.6: Conclusion
References
Part 6: Retrospective correction
Chapter 17: Retrospective correction of motion in MR images
Abstract
17.1: Retrospective correction
17.2: Applying corrections
17.3: Determining motion
17.4: Adoption of retrospective methods
17.5: Summary
References
Chapter 18: Effects of motion in sparsely sampled acquisitions
Abstract
18.1: Introduction
18.2: Choice of k-space versus time sampling
18.3: Parallel imaging and generalized spatiotemporal models
18.4: Explicit motion estimation and motion-compensated reconstruction
18.5: Implicit motion-compensated reconstruction
18.6: Manifold regularization
18.7: Need for validation studies
References
Chapter 19: Retrospective correction of dynamic B0 field variations
Abstract
19.1: Introduction
19.2: Impact of B0 field variations
19.3: Retrospective correction of dynamic B0 fields
References
Chapter 20: Machine learning
Abstract
20.1: Introduction
20.2: Image-based motion correction
20.3: Motion correction based on raw data
20.4: Outlook
References
Part 7: Prospective correction
Chapter 21: Prospective motion correction
Abstract
21.1: Introduction
21.2: Theory of prospective motion correction
21.3: Implementation of prospective motion correction
21.4: Challenges and advantages of prospective motion correction
21.5: Rejection and reacquisition
21.6: Conclusions and outlook
References
Chapter 22: Prospective B0 correction
Abstract
22.1: Motion-induced fluctuations in the magnetic field
22.2: Advantages of prospective B0 field correction
22.3: Hardware for prospective B0 updating
22.4: Approaches for prospective updating
22.5: Prospective B0 updating in different sequences
22.6: Conclusion
References
Part 8: Clinical applications beyond the brain
Chapter 23: Body imaging
Abstract
23.1: Introduction
23.2: Multidirectional motion
23.3: Bidirectional motion
23.4: Emerging techniques for motion correction
References
Chapter 24: MR motion correction in musculoskeletal imaging
Abstract
24.1: Introduction
24.2: Motion artifact mitigation strategies
24.3: Dynamic MR in musculoskeletal imaging
Summary
References
Chapter 25: Cardiac imaging
Abstract
25.1: Introduction
25.2: Motion minimization strategies
25.3: Coronary magnetic resonance angiography
25.4: Cine
25.5: Cardiac quantitative mapping
25.6: First-pass perfusion
25.7: Late gadolinium enhancement
25.8: Flow
25.9: Concluding remarks
References
Part 9: Technical applications by method
Chapter 26: MR Spectroscopy (MRS), Chemical Exchange Saturation Transfer (CEST), and Magnetization Transfer (MT)
Abstract
26.1: Introduction
26.2: Motion correction in MRS
26.3: Motion correction in CEST MR
26.4: Conclusions and future directions
References
Chapter 27: High-resolution structural brain imaging
Abstract
27.1: Introduction
27.2: State-of-the-art
27.3: Open challenges and limitations
References
Chapter 28: Amplified MRI and physiological brain tissue motion
Abstract
28.1: Introduction
28.2: Methodology
28.3: Clinical applications of amplified brain motion
28.4: Summary
References
Chapter 29: Diffusion imaging
Abstract
29.1: Introduction
29.2: MRI with sensitivity to microscopic motion
29.3: Short-term subject motion
29.4: Long-term subject motion
29.5: Summary and future perspectives
References
Further reading
Chapter 30: Non-cartesian imaging
Abstract
30.1: Introduction
30.2: Aliasing properties
30.3: Trajectories
30.4: Reconstruction
30.5: Motion compensation and synchronization
30.6: Applications
30.7: Conclusion
References
Chapter 31: Functional MRI
Abstract
31.1: Introduction
31.2: Kinds of brain motion
31.3: Identifying motion in fMRI
31.4: Influence of motion on fMRI signals
31.5: Consequences of motion for fMRI
31.6: Correlates of motion in fMRI
31.7: Amelioration of motion artifact
31.8: Prospective motion correction in fMRI
31.9: Image reconstruction errors in fMRI data caused by motion
31.10: Conclusions
Conflict of interest
References
Part 10: Special applications
Chapter 32: Fetal and placental imaging
Abstract
32.1: Introduction
32.2: Fetal imaging
32.3: Placental imaging
32.4: Summary and future directions
References
Chapter 33: Special considerations for unsedated MR in the young pediatric population
Abstract
33.1: Introduction
33.2: Strategies for successful unsedated MR studies
33.3: Conclusions
Acknowledgments
Appendix
Referencess
Chapter 34: MR-assisted PET motion correction in PET/MR
Abstract
34.1: Introduction
34.2: Approaches to use MR-derived motion estimates for PET data motion correction
34.3: Proof-of-principle studies that demonstrated technical feasibility
34.4: Potential benefits of motion correction in research and clinical PET/MR studies
34.5: Conclusion
References
Chapter 35: Small animal imaging
Abstract
35.1: Introduction
35.2: Animal handling
35.3: Hardware
35.4: Motion synchronization/compensation
35.5: Reconstruction approaches and sequences
35.6: Applications
35.7: Conclusion
References
Index

Andre van der Kouwe

André van der Kouwe, Ph.D. is Associate Professor of Radiology at the Athinoula A. Martinos Center for Biomedical Imaging in the Department of Radiology of Massachusetts General Hospital and Harvard Medical School. Dr. van der Kouwe studied electronic and bioengineering at the University of Pretoria in South Africa where he developed a brain-computer interface using brain electrical evoked signals. He received a Ph.D. in Biomedical Engineering from the Ohio State University, having developed a continuous brain electrophysiology monitoring system for critically ill patients in the neurointensive care unit at the Cleveland Clinic Foundation. He completed a research fellowship in magnetic resonance imaging at the Martinos Center where he continues to develop pulse sequences and image reconstruction software for tracking and correcting motion and related effects in magnetic resonance imaging and spectroscopy, along with acquisition methods for brain morphometry and ultra-high resolution brain tissue imaging, which he shares with the research community. Dr. van der Kouwe values his collaboration with colleagues at the Cape Universities Body Imaging Centre at the University of Cape Town who study brain disorders relevant to global health, including the effects on the developing brain of prenatal alcohol exposure and exposure to the human immunodeficiency virus and antiretroviral drugs in neonates and children.

Affiliations and expertise

Associate Professor, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

Jalal B. Andre

Jalal Andre, M.D. is Associate Professor of Radiology at the University of Washington School of Medicine and a practicing diagnostic neuroradiologist who holds current clinical privileges at the Seattle Cancer Care Alliance and the University of Washington, Harborview, and Northwest Medical Centers. He is a Diplomate for the American Board of Radiology and holds a Certificate of Additional Qualification in diagnostic neuroradiology. Dr. Andre received a Doctor of Medicine degree at Drexel University College of Medicine. He completed a preliminary year in internal medicine at Albert Einstein Medical Center in Philadelphia, PA, followed by four-year residency training in diagnostic radiology at Monmouth Medical Center in Long Branch, NJ, and two-year fellowship training in diagnostic neuroradiology at Stanford Medical Center (Stanford, CA), which included collaboration in several translational research projects in diffusion weighted imaging, arterial spin labeling and perfusion weighted imaging. Dr Andre’s primary research interests have focused on evaluating and quantifying motion in clinical MRI scans, and on perfusion and diffusion-based techniques as applied to cerebrovascular accidents, traumatic brain injury, and primary brain tumors (including glioblastoma). Dr. Andre was the recipient of the 2016 Radiological Society of North America’s Research Scholar Grant for his project entitled, “Evaluating the Prevalence, Temporal Etiology, and Cost of Patient Motion During Clinical MR Examinations”.

Affiliations and expertise

Associate Professor, Department of Radiology, University of Washington, School of Medicine, Seattle, WA, USA

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