Accelerated point spread function mapping using signal modeling for accurate echo-planar imaging geometric distortion correction

Model-based iterative reconstruction for direct imaging with point spread function encoded echo planar MRI

BACKGROUND

Echo planar imaging (EPI) is a fast measurement technique commonly used in magnetic resonance imaging (MRI), but is highly sensitive to measurement non-idealities in reconstruction. Point spread function (PSF)-encoded EPI is a multi-shot strategy which alleviates distortion, but acquisition of encodings suitable for direct distortion-free imaging prolongs scan time. In this work, a model-based iterative reconstruction (MBIR) framework is introduced for direct imaging with PSF-EPI to improve image quality and acceleration potential.

METHODS

An MBIR platform was developed for accelerated PSF-EPI. The reconstruction utilizes a subspace representation, is regularized to promote local low-rankedness (LLR), and uses variable splitting for efficient iteration. Comparisons were made against standard reconstructions from prospectively accelerated PSF-EPI data and with retrospective subsampling. Exploring aggressive partial Fourier acceleration of the PSF-encoding dimension, additional comparisons were made against an extension of Homodyne to direct PSF-EPI in numerical experiments. A neuroradiologists' assessment was completed comparing images reconstructed with MBIR from retrospectively truncated data directly against images obtained with standard reconstructions from non-truncated datasets.

RESULTS

Image quality results were consistently superior for MBIR relative to standard and Homodyne reconstructions. As the MBIR signal model and reconstruction allow for arbitrary sampling of the PSF space, random sampling of the PSF-encoding dimension was also demonstrated, with quantitative assessments indicating best performance achieved through nonuniform PSF sampling combined with partial Fourier. With retrospective subsampling, MBIR reconstructs high-quality images from sub-minute scan datasets. MBIR was shown to be superior in a neuroradiologists' assessment with respect to three of five performance criteria, with equivalence for the remaining two.

CONCLUSIONS

A novel image reconstruction framework is introduced for direct imaging with PSF-EPI, enabling arbitrary PSF space sampling and reconstruction of diagnostic-quality images from highly accelerated PSF-encoded EPI data.

Distortion correction of echo planar images applying the concept of finite rate of innovation to point spread function mapping (FRIP)

OBJECTIVE

Point spread function (PSF) mapping enables estimating the displacement fields required for distortion correction of echo planar images. Recently, a highly accelerated approach was introduced for estimating displacements from the phase slope of under-sampled PSF mapping data. Sampling schemes with varying spacing were proposed requiring stepwise phase unwrapping. To avoid unwrapping errors, an alternative approach applying the concept of finite rate of innovation to PSF mapping (FRIP) is introduced, using a pattern search strategy to locate the PSF peak, and the two methods are compared.

MATERIALS AND METHODS

Fully sampled PSF data was acquired in six subjects at 3.0 T, and distortion maps were estimated after retrospective under-sampling. The two methods were compared for both previously published and newly optimized sampling patterns. Prospectively under-sampled data were also acquired. Shift maps were estimated and deviations relative to the fully sampled reference map were calculated.

RESULTS

The best performance was achieved when using FRIP with a previously proposed sampling scheme. The two methods were comparable for the remaining schemes. The displacement field errors tended to be lower as the number of samples or their spacing increased.

CONCLUSION

A robust method for estimating the position of the PSF peak has been introduced.

EPI Nyquist ghost and geometric distortion correction by two-frame phase labeling

PURPOSE

To develop a new Nyquist ghost and geometric distortion correction method in echo planar imaging (EPI) using parallel imaging.

METHODS

Two frames of EPI data are acquired with normal and phase-labeled sequence. The phase label is applied by modifying the PE prephase gradient to shift the central echo by one echo spacing. GRAPPA weights are trained from both frames and used to reconstruct images from positive or negative echoes in each frame to remove Nyquist ghost. Geometric distortion is then corrected by the B₀ field map generated from the phase difference between positive and negative echo images. Phantom and in vivo experiments at 7 Tesla (T) and 3T were performed to evaluate the proposed method.

RESULTS

Nyquist ghost was greatly reduced in all images even under oblique imaging and poor eddy current conditions, yielding significant improvements over the existing reference scan and image entropy minimization based methods. Image geometries were fully restored after distortion correction. Phantom results indicated that the signal-to-noise ratio efficiency was largely preserved while fMRI results showed no apparent degradation of temporal resolution.

CONCLUSION

The proposed method provides robust correction of both Nyquist ghost and geometric distortion in EPI, and it is particularly suitable for dynamic EPI applications. Magn Reson Med 77:1749-1761, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Voxel spread function method for correction of magnetic field inhomogeneity effects in quantitative gradient-echo-based MRI

PURPOSE

Macroscopic magnetic field inhomogeneities adversely affect different aspects of MRI images. In quantitative MRI when the goal is to quantify biological tissue parameters, they bias and often corrupt such measurements. The goal of this article is to develop a method for correction of macroscopic field inhomogeneities that can be applied to a variety of quantitative gradient-echo-based MRI techniques.

METHODS

We have reanalyzed a basic theory of gradient echo MRI signal formation in the presence of background field inhomogeneities and derived equations that allow for correction of magnetic field inhomogeneity effects based on the phase and magnitude of gradient echo data. We verified our theory by mapping effective transverse relaxation rate in computer simulated, phantom, and in vivo human data collected with multi-gradient echo sequences.

RESULTS

The proposed technique takes into account voxel spread function effects and allowed obtaining virtually free from artifacts effective transverse relaxation rate maps for all simulated, phantom and in vivo data except of the edge areas with very steep field gradients.

CONCLUSION

The voxel spread function method, allowing quantification of tissue specific effective transverse relaxation rate-related tissue properties, has a potential to breed new MRI biomarkers serving as surrogates for tissue biological properties similar to longitudinal and transverse relaxation rate constants widely used in clinical and research MRI.