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

Area of Science:

• Magnetic Resonance Imaging
• Biomedical Engineering
• Spectroscopy

Background:

• ¹⁹ F-MRI is increasingly used for in vivo cell tracking and inflammation quantification.
• Multicolor ¹⁹ F-MRI allows simultaneous imaging of multiple fluorinated compounds.
• Separating signals and removing chemical shift artifacts are key challenges.

Purpose of the Study:

• To introduce an iterative sparse deconvolution method for multicolor ¹⁹ F-MRI.
• To enable simultaneous separation of different ¹⁹ F compounds.
• To remove chemical shift artifacts in ¹⁹ F-MRI.

Main Methods:

• Iterative sparse deconvolution applied to ¹⁹ F-MRI data.
• Cycling of readout gradient direction to alternate artifact orientation.
• Validation using numerical simulations, phantom experiments (PFCE, PFOB), and in vivo mouse models.

Main Results:

• Efficient separation of ¹⁹ F compounds demonstrated, even at low signal-to-noise ratios.
• Successful removal of chemical shift artifacts and signal separation in phantoms and in vivo.
• Excellent correlation between signal intensity and relative ¹⁹ F compound concentrations (r² = 0.966/0.990).

Conclusions:

• The developed method effectively separates ¹⁹ F compounds and removes chemical shift artifacts.
• Minimal sequence adaptation allows easy implementation on various MRI systems.
• The technique holds promise for simultaneous imaging of ¹⁹ F probes and ¹⁹ F-labeled cells.