  Purpose: To develop new encoding and reconstruction techniques for fast
multi-contrast quantitative imaging. Methods: The recently proposed Echo Planar
Time-resolved Imaging (EPTI) technique can achieve fast distortion- and
blurring-free multi-contrast quantitative imaging. In this work, a subspace
reconstruction framework is developed to improve the reconstruction accuracy of
EPTI at high encoding accelerations. The number of unknowns in the
reconstruction is significantly reduced by modeling the temporal signal
evolutions using low-rank subspace. As part of the proposed reconstruction
approach, a B0-update algorithm and a shot-to-shot B0 variation correction
method are developed to enable the reconstruction of high-resolution tissue
phase images and to mitigate artifacts from shot-to-shot phase variations.
Moreover, the EPTI concept is extended to 3D k-space for 3D GE-EPTI, where a
new temporal-variant of CAIPI encoding is proposed to further improve
performance. Results: The effectiveness of the proposed subspace reconstruction
was demonstrated first in 2D GESE EPTI, where the reconstruction achieved
higher accuracy when compared to conventional B0-informed GRAPPA. For 3D
GE-EPTI, a retrospective undersampling experiment demonstrates that the new
temporal-variant CAIPI encoding can achieve up to 72x acceleration with close
to 2x reduction in reconstruction error when compared to conventional
spatiotemporal-CAIPI encoding. In a prospective undersampling experiment,
high-quality whole-brain T2* and QSM maps at 1 mm isotropic resolution was
acquired in 52 seconds at 3T using 3D GE-EPTI with temporal-variant CAIPI
encoding. Conclusion: The proposed subspace reconstruction and optimized
temporal-variant CAIPI encoding can further improve the performance of EPTI for
fast quantitative mapping.
