Robust retrospective motion correction of head motion using navigator-based and markerless motion tracking techniques

Purpose This study investigated the artifacts arising from different types of head motion in brain MR images and how well these artifacts can be compensated using retrospective correction based on two different motion-tracking techniques. Methods MPRAGE images were acquired using a 3 T MR scanner on a cohort of nine healthy participants. Subjects moved their head to generate circular motion (4 or 6 cycles/min), stepwise motion (small and large) and “simulated realistic” motion (nodding and slow diagonal motion), based on visual instructions. One MPRAGE scan without deliberate motion was always acquired as a “no motion” reference. Three dimensional fat-navigator (FatNavs) and a Tracoline markerless device (TracInnovations) were used to obtain motion estimates and images were separately reconstructed retrospectively from the raw data based on these different motion estimates. Results Image quality was recovered from both motion tracking techniques in our stepwise and slow diagonal motion scenarios in almost all cases, with the apparent visual image quality comparable to the no-motion case. FatNav-based motion correction was further improved in the case of stepwise motion using a skull masking procedure to exclude non-rigid motion of the neck from the co-registration step. In the case of circular motion, both methods struggled to correct for all motion artifacts. Conclusion High image quality could be recovered in cases of stepwise and slow diagonal motion using both motion estimation techniques. The circular motion scenario led to more severe image artifacts that could not be fully compensated by the retrospective motion correction techniques used

Multiple Overlapping k-Space Junctions for Investigating Translating Objects (MOJITO)

It is a well-known property in Fourier transform magnetic resonance imaging (MRI) that rigid body translational motion in image space results in linear phase accumulation in k -space. This work describes Multiple Overlapping k -space Junctions for Investigating Translating Objects (MOJITO), a correction scheme based on phase differences at trajectory intersections caused by 2-D alterations in the position of an object during MR imaging. The algorithm allows both detection and correction of motion artifacts caused by 2-D rigid body translational motion. Although similar in concept to navigator echoes, MOJITO does not require a repeating path through k -space, uses k -space data from a broader region of k -space, and uses the repeated data in image reconstruction; this provides the potential for a highly efficient self-navigating motion correction method. Here, the concept and theoretical basis of MOJITO is demonstrated using the continuous sampling BOWTIE trajectory in simulation and MR experiments. This particular trajectory is selected since it is well suited for such an algorithm due to numerous trajectory intersections. Specifically, the validity of the technique in the presence of noise and off-resonance effects is demonstrated through simulation

Doctor of Philosophy

dissertationEach year in the United States, a quarter million cases of stroke are caused directly by atherosclerotic disease of the cervical carotid artery. This represents a significant portion of health care costs that could be avoided if high-risk carotid artery lesions could be detected early on in disease progression. There is mounting evidence that Magnetic Resonance Imaging of the carotid artery can better classify subjects who would benefit from interventions. Turbo Spin Echo sequences are a class of Magnetic Resonance Imaging sequences that provide a variety of tissue contrasts. While high resolution Turbo Spin Echo images have demonstrated important details of carotid artery morphology, it is evident that pulsatile blood and wall motion related to the cardiac cycle are still significant sources of image degradation. In addition, patient motion artifacts due to the relatively long scan times of Turbo Spin Echo sequences result in an unacceptable fraction of noninterpretable studies. This dissertation presents work done to detect and correct for types of voluntary and physiological patient motion