An Exploration of Motion-Sampling Interactions in 3D MRI for Neuroimaging.

Area of Science:

• Medical Imaging
• Biophysics
• Magnetic Resonance Imaging

Background:

• Motion artifacts are a significant challenge in 3D MRI, degrading image quality.
• Understanding the relationship between head motion and k-space sampling is crucial for artifact mitigation.

Purpose of the Study:

• To investigate the interaction between rigid head motion and 3D MRI k-space sampling strategies.
• To introduce motion-sampling plots as a predictive framework for MRI motion artifacts.

Main Methods:

• Evaluated various motion-sampling combinations across Cartesian, stack-of-stars, and kooshball trajectories.
• Conducted simulations and in vivo experiments with healthy volunteers using real-time pose tracking.
• Utilized motion-sampling plots to map motion states onto k-space and correlate with artifact appearance.

Main Results:

• Identified nine categories of motion artifacts, dependent on k-space motion state distribution.
• Motion-sampling plots effectively predicted artifact appearance, with findings supported by in vivo data.
• Artifacts were most severe with motion discontinuities near k-space center or aligned with slow phase-encoding directions.

Conclusions:

• Motion-sampling plots provide a powerful tool for visualizing and interpreting 3D MRI motion artifacts.
• This framework facilitates systematic evaluation of motion robustness and guides the development of motion correction techniques.
• Proposed practical recommendations for designing motion experiments to enhance reproducibility in MRI research.