Quantifying <scp>3D</scp> MR fingerprinting (<scp>3D‐MRF</scp>) reproducibility across subjects, sessions, and scanners automatically using <scp>MNI</scp> atlases
Andrew Dupuis, Yong Chen, Michael S. Hansen, Kelvin Chow, Jessie Sun, Chaitra Badve, Dan Ma, Mark A. Griswold, Rasim Boyacıoğlu
Abstract
Abstract Purpose Quantitative MRI techniques such as MR fingerprinting (MRF) promise more objective and comparable measurements of tissue properties at the point‐of‐care than weighted imaging. However, few direct cross‐modal comparisons of MRF's repeatability and reproducibility versus weighted acquisitions have been performed. This work proposes a novel fully automated pipeline for quantitatively comparing cross‐modal imaging performance in vivo via atlas‐based sampling. Methods We acquire whole‐brain 3D‐MRF, turbo spin echo, and MPRAGE sequences three times each on two scanners across 10 subjects, for a total of 60 multimodal datasets. The proposed automated registration and analysis pipeline uses linear and nonlinear registration to align all qualitative and quantitative DICOM stacks to Montreal Neurological Institute (MNI) 152 space, then samples each dataset's native space through transformation inversion to compare performance within atlas regions across subjects, scanners, and repetitions. Results Voxel values within MRF‐derived maps were found to be more repeatable (σ T1 = 1.90, σ T2 = 3.20) across sessions than vendor‐reconstructed MPRAGE (σ T1w = 6.04) or turbo spin echo (σ T2w = 5.66) images. Additionally, MRF was found to be more reproducible across scanners (σ T1 = 2.21, σ T2 = 3.89) than either qualitative modality (σ T1w = 7.84, σ T2w = 7.76). Notably, differences between repeatability and reproducibility of in vivo MRF were insignificant, unlike the weighted images. Conclusion MRF data from many sessions and scanners can potentially be treated as a single dataset for harmonized analysis or longitudinal comparisons without the additional regularization steps needed for qualitative modalities.