Improving B1+‐inhomogeneity tolerance by resolving non‐bijection in MP2RAGE R 1 mapping: A 2D look‐up table approach demonstrated at 3 T
Year: 2024
Type: article
Abstract: Purpose Regarding in vivo, robust R 1 -mapping, the goal of the present paper is twofold. First, to verify that non-bijective mapping in MP2RAGE imaging can be resolved through a 2D look-up-table approach. Second, that the expanded parameter space from this can be used to improve B 1 + -inhomogeneity tolerance without other prerequisites. Theory By deriving a second contrast from the magnitude images of the MP2RAGE acquisition, ambiguities in the original MP2RAGE image resulting from non-bijective transfer curves can be resolved. Such ambiguities may occur when protocols are optimised, e.g., for higher B 1 + -inhomogeneity tolerance. A 2D look-up-table approach combines the available information to resolve these ambiguities during mapping. Methods At 3T, we acquired MP2RAGE images with standard acquisition parameters and (non-bijective) parameters optimised for B 1 + -inhomogeneity tolerance. From three subjects across multiple sessions, we assessed the B 1 + -inhomogeneity tolerance through excitation pulse amplitude scalings. Results The R 1 -maps resulting from the B 1 + -optimised protocols showed greatly reduced B 1 + -effects across images, but without additional scanner time. Meanwhile these maps could only successfully be derived by a 2D look-up-table approach. Conclusion We show that it is possible to optimise for B 1 + -inhomogeneity tolerance in MP2RAGE through sequence parameter settings, while still successfully estimating the R 1 -map with a 2D look-up-table approach. This without the need for an additional B 1 + -map. The increased parameter space enabled by the 2D look-up-table approach may further be used to adjust MP2RAGE acquisitions for improved scan times, SNR and/or CNR.
Source: Magnetic Resonance in Medicine
DOI: 10.1002/mrm.30363
Institution: Aarhus University
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,500
Funders: Lundbeckfonden, H. Lundbeck A/S
OpenAlex ID: W4404287458
