Abstract
PURPOSE: MR fingerprinting (MRF) sequences permit efficient T(1) and T(2) estimation in cranial and extracranial regions, but these areas may include substantial fat signals that bias T(1) and T(2) estimates. MRI fat signal fraction estimation is also a topic of active research in itself, but may be complicated by B(0) heterogeneity and blurring during spiral k-space acquisitions, which are commonly used for MRF. An MRF method is proposed that separates fat and water signals, estimates water T(1) and T(2), and accounts for B(0) effects with spiral blurring correction, in a single sequence. THEORY AND METHODS: A k-space-based fat-water separation method is further extended to unbalanced steady-state free precession MRF with swept echo time. Repeated application of this k-space fat-water separation to demodulated forms of the measured data allows a B(0) map and correction to be approximated. The method is compared with MRF without fat separation across a broad range of fat signal fractions (FSFs), water T(1)s and T(2)s, and under heterogeneous static fields in simulations, phantoms, and in vivo. RESULTS: The proposed method's FSF estimates had a concordance correlation coefficient of 0.990 with conventional measurements, and reduced biases in the T(1) and T(2) estimates due to fat signal relative to other MRF sequences by several hundred ms. The B(0) correction improved the FSF, T(1), and T(2) estimation compared to those estimates without correction. CONCLUSION: The proposed method improves MRF water T(1) and T(2) estimation in the presence of fat and provides accurate FSF estimation with inline B(0) correction.