PDFF and R2* Reconstruction Error Mapping using Cramér-Rao Lower Bounds for Quality Assessment In-Vivo

Image analysts would welcome a measure of proton density fat fraction (PDFF) and R2* mapping error for image quality assessment in-vivo. This work adopts prior methodology using Cramér-Rao lower bound formulation and applies it to PDFF and R2* precision mapping in-vivo. The method is demonstrated in a software phantom and on one subject with fatty liver. The calculated maps agree with the ground truth and are informative in regions where the reconstruction signal model holds. The method should be extended to calculation of PDFF error maps.