Motion Compensation: Pulse Sequence & Reconstruction Strategies
Pelin Aksit Ciris1

1Biomedical Engineering, Akdeniz University, Antalya, Turkey

Synopsis

MRI is slow relative to the time scale of patient motion. Fundamentals of spin physics restrict scan times for most applications to the order of several seconds to minutes. Demand for higher resolution isotropic volumes has further increased acquisition times for some scans. Motion over the course of an MR acquisition has the potential to corrupt imaging data. This talk will describe potential sources of motion and their impact on MR data, then review conventional and emerging strategies for pulse sequence and reconstruction strategies for motion compensation. Advantages and disadvantages of various methods will be discussed.

Sources of motion during MR include physiological motions, such as:

  • Cardiac, Respiratory, Peristalsis, Flow (blood, CSF), Fetal motion, Bulk patient motion

Types of motion during MR can be classified as:

  • Translations, rotations, non-rigid body motions.

Timing of motion relative to the MR acquisition influences the impact of motion on MR data (amplitude and/or phase):

  • Intra-view: motion occurring within data acquisition segments, can cause dephasing and ghosting, e.g. blood flow
  • Inter-view: motion between data acquisition segments, can cause blurring and/or ghosting, depending on periodicity
  • Other: e.g. intra-shot motion in DWI, can cause phase errors

Motion Compensation Strategies: minimize the impact of motion on MR data. Immobilization aims to minimize motion via physical restraints, breath-holding, sedation or other pharmaceuticals (e.g. for quieting bowels). Pulse Sequence & Reconstruction Strategies for motion compensation can be loosely categorized as follows (with some overlap and combinations of several approaches typically being utilized):

  1. Reducing sensitivity to motion:
  • Gradient moment nulling to reduce flow dephasing;
  • Saturation bands to exclude motion sources, e.g. artifacts from blood flow or swallowing;
  • View ordering techniques to minimize the impact of motion;
  • Alternative k-space trajectories for improved motion robustness, e.g. radial, spiral, cones

2. Detecting and synchronizing acquisition to motion: Triggering/gating to motion event to effectively “freeze” motion;

  • cardiac gating, respiratory triggering;
  • prospective and retrospective

3. Detecting and correcting for motion:

  • Interleaved navigator echoes (pencil-beam, spherical, orbital, cloverleaf navigators, slice/slab tracking);
  • Low-resolution image-based navigators;
  • Self-gating using motion information inherent in data, e.g. radial, spiral, DC detection

4. Minimizing time over which motion can occur:

  • Fast pulse sequences: e.g. single-shot FSE, multi-shot EPI;
  • Under-sampling: Partial Fourier, fractional echo, parallel imaging, compressed sensing, simultaneous multi-slice imaging

5. Model-based estimation/prediction of motion

Acknowledgements

No acknowledgement found.

References

No reference found.
Proc. Intl. Soc. Mag. Reson. Med. 26 (2018)