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Abstract #4224

Fluorine Nanoparticle Quantification in a Mouse Model of Neuroinflammation: Reference-Based Bias Correction for Conventional and Compressed Sensing Reconstructions

Ludger Starke1, Andreas Pohlmann1, Thoralf Niendorf1,2,3, and Sonia Waiczies1

1Berlin Ultrahigh Field Facility, Max-Delbrück-Center for Molecular Medicine, Berlin, Germany, 2MRI.TOOLS GmbH, Berlin, Germany, 3Experimental and Clinical Research Center (ECRC), Charité Berlin, Berlin, Germany

Fluorine-19 MRI has emerged as a promising tool for in vivo cell tracking, yet low achievable signal-to-noise ratios remain a major challenge. Compressed sensing offers increased sensitivity at the cost of introducing signal intensity bias. We show that at low signal levels the quantification performance of compressed sensing is similar to conventional methods due to signal intensity distribution induced bias effects, which also affect the Fourier reconstruction. To improve quantification results, we propose an intensity correction scheme based on ex vivo reference data.

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