Premium
Precision‐guided sampling schedules for efficient T1ρ mapping
Author(s) -
Johnson Casey P.,
Thedens Daniel R.,
Magnotta Vincent A.
Publication year - 2015
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.24518
Subject(s) - imaging phantom , sampling (signal processing) , computer science , noise (video) , algorithm , artificial intelligence , nuclear medicine , computer vision , medicine , filter (signal processing) , image (mathematics)
Purpose To describe, assess, and implement a simple precision estimation framework for optimization of spin‐lock time (TSL) sampling schedules for quantitative T1ρ mapping using a mono‐exponential signal model. Materials and Methods A method is described for estimating T1ρ precision, and a cost function based on the precision estimates is evaluated to determine efficient TSL sampling schedules. The validity of the framework was tested by imaging a phantom with various sampling schedules and comparing theoretical and experimental precision values. The method utility was demonstrated with in vivo T1ρ mapping of brain tissue using a similar procedure as the phantom experiment. To assist investigators, optimal sampling schedules are tabulated for various tissue types and an online calculator is implemented. Results Theoretical and experimental precision values followed similar trends for both the phantom and in vivo experiments. The mean absolute percentage error (MAPE) of theoretical estimates of T1ρ map signal‐to‐noise ratio (SNR) was typically 5% in the phantom experiment and 33% in the in vivo demonstration. In both experiments, optimal TSL schedules yielded greater T1ρ map SNR efficiency than typical schedules. Conclusion The framework can be used to improve the imaging efficiency of T1ρ mapping protocols and to guide selection of imaging parameters. J. Magn. Reson. Imaging 2015;41:242–250. © 2014 Wiley Periodicals, Inc .