An iterative sparse deconvolution method for simultaneous multicolor 19F-MRI of multiple contrast agents

Purpose: 19F-MRI is gaining widespread interest for cell tracking and quantification of immune and inflammatory cells in vivo. Different fluorinated compounds can be discriminated based on their characteristic MR spectra, allowing in vivo imaging of multiple 19F compounds simultaneously, so-called multicolor 19F-MRI. We introduce a method for multicolor 19F-MRI using an iterative sparse deconvolution method to separate different 19F compounds and remove chemical shift artifacts arising from multiple resonances. Methods: The method employs cycling of the readout gradient direction to alternate the spatial orientation of the off-resonance chemical shift artifacts, which are subsequently removed by iterative sparse deconvolution. Noise robustness and separation was investigated by numerical simulations. Mixtures of fluorinated oils (PFCE and PFOB) were measured on a 7T MR scanner to identify the relation between 19F signal intensity and compound concentration. The method was validated in a mouse model after intramuscular injection of fluorine probes, as well as after intravascular injection. Results: Numerical simulations show efficient separation of 19F compounds, even at low signal-to-noise ratio. Reliable chemical shift artifact removal and separation of PFCE and PFOB signals was achieved in phantoms and in vivo. Signal intensities correlated excellently to the relative 19F compound concentrations (r−2 = 0.966/0.990 for PFOB/PFCE). Conclusions: The method requires minimal sequence adaptation and is therefore easily implemented on different MRI systems. Simulations, phantom experiments, and in-vivo measurements in mice showed effective separation and removal of chemical shift artifacts below noise level. We foresee applicability for simultaneous in-vivo imaging of 19F-containing fluorine probes or for detection of 19F-labeled cell populations.