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B(1) inhomogeneity correction of RARE MRI at low SNR: quantitative in vivo (19)F MRI of mouse neuroinflammation with a cryogenically-cooled transceive surface radiofrequency probe

Authors

  • P.R. Delgado
  • A. Kuehne
  • M. Aravina
  • J.M. Millward
  • A. Vázquez
  • L. Starke
  • H. Waiczies
  • A. Pohlmann
  • T. Niendorf
  • S. Waiczies

Journal

  • Magnetic Resonance in Medicine

Citation

  • Magn Reson Med

Abstract

  • PURPOSE: Low SNR in fluorine-19 (19F) MRI benefits from cryogenically-cooled transceive surface RF probes (CRPs), but strong B(1) 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 B(1) 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 B(1) 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 T(1) calculations for (19)F-nanoparticles during pathology and B(1) 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.


DOI

doi:10.1002/mrm.29094