Low SNR in fluorine-19 (19 F) MRI benefits from cryogenically-cooled transceive surface RF probes (CRPs), but strong B1 inhomogeneities hinder quantification. Rapid acquisition with refocused echoes (RARE) is an SNR-efficient method for MRI of neuroinflammation with perfluorinated compounds but lacks an analytical signal intensity equation to retrospectively correct B1 inhomogeneity. Here, a workflow was proposed and validated to correct and quantify 19 F-MR signals from the inflamed mouse brain using a 19 F-CRP. In vivo 19 F-MR images were acquired in a neuroinflammation mouse model with a quadrature 19 F-CRP using an imaging setup including 3D-printed components to acquire co-localized anatomical and 19 F images. Model-based corrections were validated on a uniform 19 F phantom and in the neuroinflammatory model. Corrected 19 F-MR images were benchmarked against reference images and overlaid on in vivo 1 H-MR images. Computed concentration uncertainty maps using Monte Carlo simulations served as a measure of performance of the B1 corrections. Our study reports on the first quantitative in vivo 19 F-MR images of an inflamed mouse brain using a 19 F-CRP, including in vivo T1 calculations for 19 F-nanoparticles during pathology and B1 corrections for 19 F-signal quantification. Model-based corrections markedly improved 19 F-signal quantification from errors > 50% to < 10% in a uniform phantom (p < 0.001). Concentration uncertainty maps ex vivo and in vivo yielded uncertainties that were generally < 25%. Monte Carlo simulations prescribed SNR ≥ 10.1 to reduce uncertainties < 10%, and SNR ≥ 4.25 to achieve uncertainties < 25%. Our model-based correction method facilitated 19 F signal quantification in the inflamed mouse brain when using the SNR-boosting 19 F-CRP technology, paving the way for future low-SNR 19 F-MRI applications in vivo.
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