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

Purpose: F-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 F compounds simultaneously, so-called multicolor F-MRI. We introduce a method for multicolor F-MRI using an iterative sparse deconvolution method to separate different F 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 F 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 F 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 F compound concentrations (r = 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 F-containing fluorine probes or for detection of F-labeled cell populations.