B1 inhomogeneity correction of RARE MRI at low SNR: Quantitative in vivo 19F MRI of mouse neuroinflammation with a cryogenically‐cooled transceive surface radiofrequency probe. Issue 4 (23rd November 2021)

• Record Type: Journal Article
• Authors: Delgado, Paula Ramos; Kuehne, Andre; Aravina, Mariya; Millward, Jason M.; Vázquez, Alonso; Starke, Ludger; Waiczies, Helmar; Pohlmann, Andreas; Niendorf, Thoralf; Waiczies, Sonia
• Is Part Of: Magnetic resonance in medicine. Volume 87:Issue 4(2022)
• Page Start: 1952
• Page End: 1970
• Publication Date: 2021-11-23
• Subjects: 19F‐MRI -- B1 correction -- inflammation -- RARE -- transceive surface RF probe; Nuclear magnetic resonance -- Periodicals; Electron paramagnetic resonance -- Periodicals; 616.07548
• DOI: 10.1002/mrm.29094
• Languages: English
• ISSNs: 0740-3194

Abstract

Abstract : Purpose: 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. Methods: 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. Results: 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%. Conclusion: 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.