Two dimensional intersecting k-space trajectories have been previously demonstrated to allow fast multi-spectral imaging. Repeated sampling of k-space points leads to destructive interference of the signal coming from the off-resonance spectral peaks; on resonance data reconstruction yields images of the on-resonance peak, with some of the off-resonance energy being spread as noise in the image. A shift of the k-space data by a given off-resonance frequency brings a second frequency of interest on resonance, allowing the reconstruction of a second spectral peak from the same k-space data. Given the higher signal to noise per unit time characteristic of a 3D acquisition, we have extended the concept of intersecting trajectories to three dimensions. A 3D, rosette-like, pulse sequence was designed and implemented in a clinical, 1.5T scanner. An iterative density compensation function was developed to properly weight the 3D intersecting trajectories before Fourier transformation. Three volunteers were scanned using this sequence, and separate fat and water images were reconstructed from the same imaging dataset.
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