Data-Driven Retrospective Correction of B1 Field Inhomogeneity in Fast Macromolecular Proton Fraction and R1 Mapping

Correction of B-1 field non-uniformity is critical for many quantitative MRI methods including variable flip angle (VFA) T-1 mapping and single-point macromolecular proton fraction (MPF) mapping. The latter method showed promising results as a fast and robust quantitative myelin imaging approach and involves VFA-based R-1 = 1/T-1 map reconstruction as an intermediate processing step. The need for B-1 correction restricts applications of the above methods, since B-1 mapping sequences increase the examination time and are not commonly available in clinics. A new algorithm was developed to enable retrospective data-driven simultaneous B-1 correction in VFA R-1 and single-point MPF mapping. The principle of the algorithm is based on different mathematical dependences of B-1-related errors in R-1 and MPF allowing extraction of a surrogate B1 field map from uncorrected R-1 and MPF maps. To validate the method, whole-brain R-1 and MPF maps with isotropic 1.25 mm(3) resolution were obtained on a 3 T MRI scanner from 11 volunteers. Mean parameter values in segmented brain tissues were compared between three reconstruction options including the absence of correction, actual B-1 correction, and surrogate B-1 correction. Surrogate B-1 maps closely reproduced actual patterns of B-1 inhomogeneity. Without correction, B1 non-uniformity caused highly significant biases in R-1 and MPF (P < 0.001). Surrogate B-1 field correction reduced the biases in both R-1 and MPF to a non-significant level (0.1 <= P <= 0.8). The described algorithm obviates the use of dedicated B-1 mapping sequences in fast single-point MPF mapping and provides an alternative solution for correction of B-1 non-uniformities in VFA R-1 mapping.

Automated summary

Correction of B-1 field non-uniformity is crucial for quantitative MRI methods like VFA T-1 mapping and MPF mapping. A new algorithm has been developed to retrospectively correct B-1 field in VFA R-1 and single-point MPF mapping, providing an alternative solution without the need for dedicated B-1 mapping sequences. The algorithm effectively reduces biases in R-1 and MPF values caused by B-1 non-uniformity, making it a promising approach for accurate myelin imaging.