Abstract
PURPOSE: In this work we demonstrate how sequence parameter settings influence the accuracy and precision in T1 , T2 , and off-resonance maps obtained with the PLANET method for a single-component signal model. In addition, the performance of the method for the particular case of a two-component relaxation model for white matter tissue was assessed.
METHODS: Numerical simulations were performed to investigate the influence of sequence parameter settings on the accuracy and precision in the estimated parameters for a single-component model, as well as for a two-component white matter model. Phantom and in vivo experiments were performed for validation. In addition, the effects of Gibbs ringing were investigated.
RESULTS: By making a proper choice for sequence parameter settings, accurate and precise parameter estimation can be achieved for a single-component signal model over a wide range of relaxation times at realistic SNR levels. Due to the presence of a second myelin-related signal component in white matter, an underestimation of approximately 30% in T1 and T2 was observed, predicted by simulations and confirmed by measurements. Gibbs ringing artifacts correction improved the precision and accuracy of the parameter estimates.
CONCLUSION: For a single-component signal model there is a broad "sweet spot" of sequence parameter combinations for which a high accuracy and precision in the parameter estimates is achieved over a wide range of relaxation times. For a multicomponent signal model, the single-component PLANET reconstruction results in systematic errors in the parameter estimates as expected.
Original language | English |
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Pages (from-to) | 1534-1552 |
Number of pages | 19 |
Journal | Magnetic Resonance in Medicine |
Volume | 81 |
Issue number | 3 |
DOIs | |
Publication status | Published - 1 Mar 2019 |
Keywords
- SNR
- accuracy
- phase-cycled bSSFP
- precision
- relaxometry