title: Accelerated cardiac cine MRI using locally low rank and finite difference constraints.
abstract: To evaluate the potential value of combining multiple constraints for highly accelerated cardiac cine MRI.
  
  
  
  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, 9-13s single breath hold). Reconstruction was compared against state-of-the-art constrained reconstruction methods: LLR, FD, and k-t SLR.
  
  
  
  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 2×2mm(2) and 40ms.
  
  
  
  Highly accelerated cardiac cine is enabled by the combination of 2D undersampling and the synergistic use of LLR and FD constraints.
authors.affiliation: Department of Biomedical Engineering, University of Southern California, Los Angeles, USA. Electronic address: xinm@usc.edu.
authors.forename: Xin
authors.initials: X
authors.lastname: Miao
authors.affiliation: Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, USA.
authors.forename: Sajan Goud
authors.initials: SG
authors.lastname: Lingala
authors.affiliation: Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, USA.
authors.forename: Yi
authors.initials: Y
authors.lastname: Guo
authors.affiliation: Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, USA.
authors.forename: Terrence
authors.initials: T
authors.lastname: Jao
authors.affiliation: Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.
authors.forename: Muhammad
authors.initials: M
authors.lastname: Usman
authors.affiliation: Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.
authors.forename: Claudia
authors.initials: C
authors.lastname: Prieto
authors.affiliation: Department of Biomedical Engineering, University of Southern California, Los Angeles, USA; Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, USA.
authors.forename: Krishna S
authors.initials: KS
authors.lastname: Nayak
mesh_terms: D000465:Algorithms; D062485:Breath Holding; D006321:Heart / Q000000981:diagnostic imaging* / Q000502:physiology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D019028:Magnetic Resonance Imaging, Cine / Q000379:methods*; D011446:Prospective Studies; D012189:Retrospective Studies
keywords: Cardiac cine MRI; Compressed sensing; Constrained reconstruction; Locally low rank; Parallel imaging; Sparse sampling