Motion-resolved and free-breathing liver MRF

Peng Cao, Zuojun Wang, Chenyang Liu, Tian Li, Edward S. Hui, Jing Cai (Corresponding Author)

Research output: Journal article publicationJournal articleAcademic researchpeer-review


Purpose: To develop a motion-resolved and free-breathing liver magnetic resonance fingerprinting (MRF) protocol. Methods: The deformation maps were obtained from the first singular image of MRF data. The reconstruction method enforced the consistency of the MRF data with the deformation maps by adding the deformation maps to the encoding matrix. A sliding window reconstruction was inherently assumed, with a window size of 60 repetition times (TRs) and a step size of 30 TRs. L1 wavelet regularization was applied to reduce the undersampling artifact. MRF was tested on four healthy volunteers with parameters: 13 s/slice, 0.39 s/frame, and 33 time frames/slice. Results: For measuring the accuracy of the deformation map, the typical normalized root mean square error (NRMSE) of the first singular image after motion correction was 0.19. In the sagittal scan, the liver T1 and T2 were 808.7±96.8 ms and 52.7±11.6 ms, respectively. They agreed with our previously reported values, i.e., T1 = 759 ms and T2 = 51 ms at 3 T, using free-breathing liver MRF. Compared to breath-hold MRF, the NRMSEs for T1 and T2 maps (without considering vessel pixels) from the proposed method were 0.13 and 0.18, respectively. Conclusion: We demonstrated a motion-resolved MRF with a nominal frame rate of 2.5 Hz for free-breathing liver imaging.

Original languageEnglish
Pages (from-to)69-80
Number of pages12
JournalMagnetic Resonance Imaging
Early online date26 May 2022
Publication statusPublished - Sep 2022


  • Free-breathing MRF
  • Iterative reconstruction
  • Liver MRF
  • MRF reconstruction
  • Prostate MRF

ASJC Scopus subject areas

  • Biophysics
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging


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