Deep learning-based MR fingerprinting ASL ReconStruction (DeepMARS)

Magn Reson Med. 2020 Aug;84(2):1024-1034. doi: 10.1002/mrm.28166. Epub 2020 Feb 4.

Abstract

Purpose: To develop a reproducible and fast method to reconstruct MR fingerprinting arterial spin labeling (MRF-ASL) perfusion maps using deep learning.

Method: A fully connected neural network, denoted as DeepMARS, was trained using simulation data and added Gaussian noise. Two MRF-ASL models were used to generate the simulation data, specifically a single-compartment model with 4 unknowns parameters and a two-compartment model with 7 unknown parameters. The DeepMARS method was evaluated using MRF-ASL data from healthy subjects (N = 7) and patients with Moymoya disease (N = 3). Computation time, coefficient of determination (R2 ), and intraclass correlation coefficient (ICC) were compared between DeepMARS and conventional dictionary matching (DM). The relationship between DeepMARS and Look-Locker PASL was evaluated by a linear mixed model.

Results: Computation time per voxel was <0.5 ms for DeepMARS and >4 seconds for DM in the single-compartment model. Compared with DM, the DeepMARS showed higher R2 and significantly improved ICC for single-compartment derived bolus arrival time (BAT) and two-compartment derived cerebral blood flow (CBF) and higher or similar R2 /ICC for other parameters. In addition, the DeepMARS was significantly correlated with Look-Locker PASL for BAT (single-compartment) and CBF (two-compartment). Moreover, for Moyamoya patients, the location of diminished CBF and prolonged BAT shown in DeepMARS was consistent with the position of occluded arteries shown in time-of-flight MR angiography.

Conclusion: Reconstruction of MRF-ASL with DeepMARS is faster and more reproducible than DM.

Keywords: DeepMARS; MRF-ASL; deep learning; reconstruction; reproducibility.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cerebrovascular Circulation
  • Deep Learning*
  • Humans
  • Magnetic Resonance Imaging
  • Moyamoya Disease*
  • Spin Labels

Substances

  • Spin Labels