Affiliation:
1. The Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology New York University Grossman School of Medicine New York New York USA
Abstract
AbstractPurposeTo introduce an alternative idea for fat suppression that is suited both for low‐field applications where conventional fat‐suppression approaches become ineffective due to narrow spectral separation and for applications with strong B0 homogeneities.MethodsSeparation of fat and water is achieved by sweeping the frequency of RF saturation pulses during continuous radial acquisition and calculating frequency‐resolved images using regularized iterative reconstruction. Voxel‐wise signal‐response curves are extracted that reflect tissue's response to RF saturation at different frequencies and allow the classification into fat or water. This information is then utilized to generate water‐only composite images. The principle is demonstrated in free‐breathing abdominal and neck examinations using stack‐of‐stars 3D balanced SSFP (bSSFP) and gradient‐recalled echo (GRE) sequences at 0.55 and 3T. Moreover, a potential extension toward quantitative fat/water separation is described.ResultsExperiments with a proton density fat fraction (PDFF) phantom validated the reliability of fat/water separation using signal‐response curves. As demonstrated for abdominal imaging at 0.55T, the approach resulted in more uniform fat suppression without loss of water signal and in improved CSF‐to‐fat signal ratio. Moreover, the approach provided consistent fat suppression in 3T neck exams where conventional spectrally‐selective fat saturation failed due to strong local B0 inhomogeneities. The feasibility of simultaneous fat/water quantification has been demonstrated in a PDFF phantom.ConclusionThe proposed principle achieves reliable fat suppression in low‐field applications and adapts to high‐field applications with strong B0 inhomogeneity. Moreover, the principle potentially provides a basis for developing an alternative approach for PDFF quantification.
Funder
National Institutes of Health