On the accuracy and precision of PLANET for multiparametric MRI using phase-cycled bSSFP imaging.

Purpose: In this work we demonstrate how sequence parameter settings influence the accuracy and precision in T , T , 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 T and T 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.