Accelerated cardiac cine MRI using locally low rank and finite difference constraints

Miao, Xin; Lingala, Sajan Goud; Guo, Yi; Jao, Terrence; Usman, Muhammad; Prieto, Claudia; Nayak, Krishna S.

Abstract

Purpose: To evaluate the potential value of combining multiple constraints for highly accelerated cardiac cine MRI. Methods: A locally low rank (LLR) constraint and a temporal finite difference (FD) constraint were combined to reconstruct cardiac cine data from highly undersampled measurements. Retrospectively undersampled 2D Cartesian reconstructions were quantitatively evaluated against fully-sampled data using normalized root mean square error, structural similarity index (SSIM) and high frequency error norm (HFEN). This method was also applied to 2D golden-angle radial real-time imaging to facilitate single breath-hold whole-heart cine (12 short-axis slices, 9-13 s single breath hold). Reconstruction was compared against state-of-the-art constrained reconstruction methods: LLR, FD, and k-t SLR. Results: At 10 to 60 spokes/frame, LLR + FD better preserved fine structures and depicted myocardial motion with reduced spatio-temporal blurring in comparison to existing methods. LLR yielded higher SSIM ranking than FD; FD had higher HFEN ranking than LLR. LLR + FD combined the complimentary advantages of the two, and ranked the highest in all metrics for all retrospective undersampled cases. Single breath-hold multi-slice cardiac cine with prospective undersampling was enabled with in-plane spatio-temporal resolutions of 2 x 2 mm(2) and 40 ms. Conclusion: Highly accelerated cardiac cine is enabled by the combination of 2D undersampling and the synergistic use of LLR and FD constraints. (C) 2016 Elsevier Inc. All rights reserved.

Más información

Título según WOS: ID WOS:000377640500001 Not found in local WOS DB
Título de la Revista: MAGNETIC RESONANCE IMAGING
Volumen: 34
Número: 6
Editorial: Elsevier Science Inc.
Fecha de publicación: 2016
Página de inicio: 707
Página final: 714
DOI:

10.1016/j.mri.2016.03.007

Notas: ISI