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Abstract #2862

Correcting Signal Intensity Bias in 19F MR Imaging of Inflammation by Statistical Modelling

Ludger Starke1, Thoralf Niendorf1, and Sonia Waiczies1
1Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany

Labeling cells with 19F nanoparticles (NPs) continues to elicit interest for non-invasive localization of inflammation and monitoring immune cell therapy. Systematic overestimation in low SNR MRI of 19F-NPs has been previously described which needs to be corrected for valid quantitative conclusions. We develop a statistical model which successfully compensates this bias and demonstrate its efficacy for the correct estimation of signal intensities on neuroinflammation data acquired in a mouse model of multiple sclerosis. The correction only relies on the image data itself and promises to be a valuable contribution to the development of reliable quantitative 19F MRI.

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