Subject motion during magnetic resonance imaging (MRI) has been problematic since its introduction as a clinical imaging modality. While sensitivity to particle motion or blood flow can be used to provide useful image contrast, bulk motion presents a considerable problem in the majority of clinical applications. It is one of the most frequent sources of artefacts. Over 30 years of research have produced numerous methods to mitigate or correct for motion artefacts, but no single method can be applied in all imaging situations. Instead, a ‘toolbox’ of methods exists, where each tool is suitable for some tasks, but not for others. This article reviews the origins of motion artefacts and presents current mitigation and correction methods. In some imaging situations, the currently available motion correction tools are highly effective; in other cases, appropriate tools still need to be developed. It seems likely that this multifaceted approach will be what eventually solves the motion sensitivity problem in MRI, rather than a single solution that is effective in all situations. This review places a strong emphasis on explaining the physics behind the occurrence of such artefacts, with the aim of aiding artefact detection and mitigation in particular clinical situations.
Motion correction in magnetic resonance imaging by real‐time adjustment of the imaging pulse sequence was first proposed more than 20 years ago. Recent advances have resulted from combining real‐time correction with new navigator and external tracking mechanisms capable of quantifying rigid‐body motion in all 6 degrees of freedom. The technique is now often referred to as “prospective motion correction.” This article describes the fundamentals of prospective motion correction and reviews the latest developments in its application to brain imaging and spectroscopy. Although emphasis is placed on the brain as the organ of interest, the same principles apply whenever the imaged object can be approximated as a rigid body. Prospective motion correction can be used with most MR sequences, so it has potential to make a large impact in clinical routine. To maximize the benefits obtained from the technique, there are, however, several challenges still to be met. These include practical implementation issues, such as obtaining tracking data with minimal delay, and more fundamental problems, such as the magnetic field distortions caused by a moving object. This review discusses these challenges and summarizes the state of the art. We hope that this work will motivate further developments in prospective motion correction and help the technique to reach its full potential. Magn Reson Med, 2013. © 2012 Wiley Periodicals, Inc.
Magnetic resonance imaging (MRI) is a widely used method for non-invasive study of the structure and function of the human brain. Increasing magnetic field strengths enable higher resolution imaging; however, long scan times and high motion sensitivity mean that image quality is often limited by the involuntary motion of the subject. Prospective motion correction is a technique that addresses this problem by tracking head motion and continuously updating the imaging pulse sequence, locking the imaging volume position and orientation relative to the moving brain. The accuracy and precision of current MR-compatible tracking systems and navigator methods allows the quantification and correction of large-scale motion, but not the correction of very small involuntary movements in six degrees of freedom. In this work, we present an MR-compatible tracking system comprising a single camera and a single 15 mm marker that provides tracking precision in the order of 10 m and 0.01 degrees. We show preliminary results, which indicate that when used for prospective motion correction, the system enables improvement in image quality at both 3 T and 7 T, even in experienced and cooperative subjects trained to remain motionless during imaging. We also report direct observation and quantification of the mechanical ballistocardiogram (BCG) during simultaneous MR imaging. This is particularly apparent in the head-feet direction, with a peak-to-peak displacement of 140 m.
Magnetic resonance imaging (MRI) is a widely used method for non-invasive study of the structure and function of the human brain. Increasing magnetic field strengths enable higher resolution imaging; however, long scan times and high motion sensitivity mean that image quality is often limited by the involuntary motion of the subject. Prospective motion correction is a technique that addresses this problem by tracking head motion and continuously updating the imaging pulse sequence, locking the imaging volume position and orientation relative to the moving brain. The accuracy and precision of current MR-compatible tracking systems and navigator methods allows the quantification and correction of large-scale motion, but not the correction of very small involuntary movements in six degrees of freedom. In this work, we present an MR-compatible tracking system comprising a single camera and a single 15 mm marker that provides tracking precision in the order of 10 m and 0.01 degrees. We show preliminary results, which indicate that when used for prospective motion correction, the system enables improvement in image quality at both 3 T and 7 T, even in experienced and cooperative subjects trained to remain motionless during imaging. We also report direct observation and quantification of the mechanical ballistocardiogram (BCG) during simultaneous MR imaging. This is particularly apparent in the head-feet direction, with a peak-to-peak displacement of 140 m.
Evaluation of neurodegenerative disease progression may be assisted by quantification of the volume of structures in the human brain using magnetic resonance imaging (MRI). Automated segmentation software has improved the feasibility of this approach, but often the reliability of measurements is uncertain. We have established a unique dataset to assess the repeatability of brain segmentation and analysis methods. We acquired 120 T1-weighted volumes from 3 subjects (40 volumes/subject) in 20 sessions spanning 31 days, using the protocol recommended by the Alzheimer's Disease Neuroimaging Initiative (ADNI). Each subject was scanned twice within each session, with repositioning between the two scans, allowing determination of test-retest reliability both within a single session (intra-session) and from day to day (inter-session). To demonstrate the application of the dataset, all 3D volumes were processed using FreeSurfer v5.1. The coefficient of variation of volumetric measurements was between 1.6% (caudate) and 6.1% (thalamus). Inter-session variability exceeded intra-session variability for lateral ventricle volume (P<0.0001), indicating that ventricle volume in the subjects varied between days.
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