Multicontrast Reconstruction Using Compressed Sensing With Low Rank and Spatially Varying Edge-Preserving Constraints for High-Resolution MR Characterization of Myocardial Infarction

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Abstract

Purpose:

To enable robust reconstruction for highly accelerated three-dimensional multicontrast late enhancement imaging to provide improved MR characterization of myocardial infarction with isotropic high spatial resolution.

Theory and Methods:

A new method using compressed sensing with low rank and spatially varying edge-preserving constraints (CS-LASER) is proposed to improve the reconstruction of fine image details from highly undersampled data. CS-LASER leverages the low rank feature of the multicontrast volume series in MR relaxation and integrates spatially varying edge preservation into the explicit low rank constrained compressed sensing framework using weighted total variation. With an orthogonal temporal basis pre-estimated, a multiscale iterative reconstruction framework is proposed to enable the practice of CS-LASER with spatially varying weights of appropriate accuracy.

Results:

In in vivo pig studies with both retrospective and prospective undersamplings, CS-LASER preserved fine image details better and presented tissue characteristics with a higher degree of consistency with histopathology, particularly in the peri-infarct region, than an alternative technique for different acceleration rates. An isotropic resolution of 1.5 mm was achieved in vivo within a single breath-hold using the proposed techniques.

Conclusion:

Accelerated three-dimensional multicontrast late enhancement with CS-LASER can achieve improved MR characterization of myocardial infarction with high spatial resolution.

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