Effects of Resolution and Registration Algorithm on the Accuracy of EPI vNavs for Real Time Head Motion Correction in MRI

Low-resolution, EPI-based Volumetric Navigators (vNavs) have been used as a prospective motion-correction system in a variety of MRI neuroimaging pulse sequences. The use of low-resolution volumes represents a trade-off between motion tracking accuracy and acquisition time. However, this means that registration must be accurate on the order of 0.2 voxels or less to be effective for motion correction. While vNavs have shown promising results in clinical and research use, the choice of navigator and registration algorithm have not previously been systematically evaluated. In this work we experimentally evaluate the accuracy of vNavs, and possible design choices for future improvements to the system, using real human data. We acquired navigator volumes at three isotropic resolutions (6.4 mm, 8 mm, and 10 mm) with known rotations and translations. The vNavs were then rigidly registered using trilinear, tricubic, and cubic B-spline interpolation. We demonstrate a novel refactoring of the cubic B-spline algorithm that stores pre-computed coefficients to reduce the per-interpolation time to be identical to tricubic interpolation. Our results show that increasing vNav resolution improves registration accuracy, and that cubic B-splines provide the highest registration accuracy at all vNav resolutions. Our results also suggest that the time required by vNavs may be reduced by imaging at 10 mm resolution, without substantial cost in registration accuracy.