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- Title
Optimized and accelerated <sup>19</sup>F‐MRI of inhaled perfluoropropane to assess regional pulmonary ventilation.
- Authors
Neal, Mary A.; Pippard, Benjamin J.; Hollingsworth, Kieren G.; Maunder, Adam; Dutta, Prosenjit; Simpson, A. John; Blamire, Andrew M.; Wild, James M.; Thelwall, Peter E.
- Abstract
Purpose: To accelerate 19F‐MR imaging of inhaled perfluoropropane using compressed sensing methods, and to optimize critical scan acquisition parameters for assessment of lung ventilation properties. Methods: Simulations were performed to determine optimal acquisition parameters for maximal perfluoropropane signal‐to‐noise ratio (SNR) in human lungs for a spoiled gradient echo sequence. Optimized parameters were subsequently employed for 19F‐MRI of inhaled perfluoropropane in a cohort of 11 healthy participants using a 3.0 T scanner. The impact of 1.8×, 2.4×, and 3.0× undersampling ratios on 19F‐MRI acquisitions was evaluated, using both retrospective and prospective compressed sensing methods. Results: 3D spoiled gradient echo 19F‐MR ventilation images were acquired at 1‐cm isotropic resolution within a single breath hold. Mean SNR was 11.7 ± 4.1 for scans acquired within a single breath hold (duration = 18 s). Acquisition of 19F‐MRI scans at shorter scan durations (4.5 s) was also demonstrated as feasible. Application of both retrospective (n = 8) and prospective (n = 3) compressed sensing methods demonstrated that 1.8× acceleration had negligible impact on qualitative image appearance, with no statistically significant change in measured lung ventilated volume. Acceleration factors of 2.4× and 3.0× resulted in increasing differences between fully sampled and undersampled datasets. Conclusion: This study demonstrates methods for determining optimal acquisition parameters for 19F‐MRI of inhaled perfluoropropane and shows significant reduction in scan acquisition times (and thus participant breath hold duration) by use of compressed sensing.
- Subjects
COMPRESSED sensing; LUNG volume; SIGNAL-to-noise ratio
- Publication
Magnetic Resonance in Medicine, 2019, Vol 82, Issue 4, p1301
- ISSN
0740-3194
- Publication type
Article
- DOI
10.1002/mrm.27805