Abstract #3576

Mitigating MR fingerprinting undersampling errors is more effective through sequence optimization than via low rank reconstruction

Martijn Nagtegaal^1,2, Frans Vos^2,3, Matthias J.P. van Osch¹, and David G.J. Heesterbeek^4,5

¹C.J. Gorter MRI Center, Radiology, Leiden University Medical Center, Leiden, Netherlands, ²Department of Imaging Physics, Delft University of Technology, Delft, Netherlands, ³Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands, ⁴Computational Imaging Group for MR Therapy and Diagnostics, University Medical Center Utrecht, Utrecht, Netherlands, ⁵Department of Radiotherapy, University Medical Center Utrecht, Utrecht, Netherlands

Synopsis

Keywords: MR Fingerprinting, MR Fingerprinting

Motivation: To reduce undersampling errors in MR Fingerprinting maps, both sequence optimization and low rank (LR) reconstruction methods have been proposed , but these have not been compared or combined.

Goal(s): To compare the effectiveness of LR-reconstruction and sequence optimization for reducing undersampling errors.

Approach: Undersampled 2D spiral MRF data as acquired with 7 different flip angle patterns in 6 healthy subjects are reconstructed with the standard vendor reconstruction and an in-house LR-reconstruction and compared to fully-sampled MRF T₁- and T₂-maps.

Results: Undersampling-optimized sequences showed a reduced error compared to other sequences, even after LR-reconstruction.

Impact: We show that optimized flip-angle patterns with or without LR-reconstruction outperform traditional schemes with LR reconstruction. Inclusion of LR-reconstruction in the optimization step is not essential, when designing sequences that minimize undersampling artifacts.

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