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Improved Pulmonary 129Xe Ventilation Imaging via 3D-Spiral UTE MRI1Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States, 2Philips, Cincinnati, OH, United States, 3University of Cincinnati, Cincinnati, OH, United States, 4Phoenix Children’s Hospital, Phoenix, AZ, United States, 5Mayo Clinic, Rochester, MN, United States, 6University of Cincinnati Medical Center, Cincinnati, OH, United States
Synopsis
Functional lung imaging via inhaled hyperpolarized 129Xe MRI has been shown to provide sensitive regional maps of ventilation and gas-exchange. Traditionally, ventilation images are acquired via standard Cartesian or less commonly radial sequences. Previously reported results have shown promise for 2D-spiral sequences with increased SNR and/or shorter acquisition lengths. In this study, a 3D-spiral sequence (FLORET) was implemented and compared to Cartesian, radial, and 2D-spiral acquisition techniques. This is the first implementation and comparison of a 3D-spiral UTE technique to acquire hyperpolarized gas images.
Purpose
MRI of inhaled hyperpolarized 129Xe has been shown to characterize regional ventilation in a wide variety of diseases and populations1–10. Ventilation images have most-often been acquired via Cartesian gradient-recalled-echo (GRE) sequences with thick slices (~15mm). The thick slices are implemented to fully acquire the lung volume, limit acquisition time to a breath-hold, and increase SNR. These sequences require few excitations (permitting larger RF flip angles) but suffer from relatively low resolution due to the breath-hold and gradient limitations. Additionally, some groups have begun implementing 3D-radial UTE sequences for more accurate magnetization dynamics and to better quantify ventilation physiology with isotropic resolution4,11–14. However, these sequences are inherently inefficient in k-space sampling, requiring many excitations (forcing lower flip angles for non-renewable magnetization), and may need to be acquired at lower resolution or with undersampling in order acquire within a breath-hold. Comparisons between the GRE and 3D-radial techniques have shown that 3D-radial sequences suffer a factor of ≈2 in SNR losses compared to GRE but better capture physiologically-relevant characteristics (e.g. gravitational dependence)4. In addition, UTE acquisitions allow advanced image corrections and reconstructions4,15–17.
Relative to radial sequences, spiral acquisitions sample k-space more efficiently, overcoming many of the limitations of 3D-radial sequences, while maintaining their advantages (short TE, isotropic resolution, etc.)15,18–20. Previous hyperpolarized gas spiral images have demonstrated dynamic imaging, minimal excitations, and high SNR15,20,21. However, these sequences were 2D, relying on slice selection, and thus resulting in similar limitations to Cartesian ventilation images4. Here, we demonstrate the first use of a 3D-spiral UTE sequence to acquire xenon ventilation images and compare it to standard ventilation sequences.
Methods
The 3D-spiral sequence implemented here (Fermat Looped ORthogonally Encoded Trajectories, FLORET) is based on the Fermat spiral to limit the oversampling of low k values, resulting in higher sampling efficiencies19. Each spiral is projected onto a single cone (between +45° and -45°) with two orthogonal sets of cones required to fully acquire k-space. The spiral was rotated via the golden angle and rapid gradient spoiling was implemented19. 129Xe was hyperpolarized to 30-40% via a Polarean 9820 xenon polarizer; but decayed to 15-25% at time of imaging. Comparative GRE, 3D-radial, 2D-spiral, and FLORET images were acquired in a structured phantom and in healthy adults (N=3). Images were acquired using a home-built xenon coil in less than 16s (maximum breath-hold duration). Flip angles were optimized via , dependent on the number of excitations a 129Xe nucleus would experience22. TR/TE were the shortest possible for each scan (≈2-50ms/0.09-3ms). GRE, 3D-radial, 2D-spiral, and 3D-spiral/FLORET images were acquired using the following comparisons: 1) Highest fully-sampled resolution, 2) Same voxel volume, and 3) equivalent undersampling.
Non-Cartesian acquisitions were gridded and all acquisitions were reconstructed similarly using Graphical Programming Interface23. Following 3D-FFT, UTE images were corrected for off-resonance effects, B1 inhomogeneity, and hyperpolarized signal decay.
Results
FLORET xenon ventilation imaging allowed a fully sampled image with (3.5mm)3 voxels and a (300mm)3 field of view, to be acquired in 15 seconds, a significant increase in resolution (3.15x smaller voxels) over standard sequences (Figure 1). Additionally, only 262 excitations were necessary (readout duration of 46.3ms), resulting in an SNR-optimized flip angle of 5.5°. However, if the receiver frequency is set imperfectly, the resulting images will exhibit off-resonance blurring/distortion due to the long readout (Figure 2). This can be fixed post-acquisition via off-resonance focusing24.
The standard GRE acquisition had an SNR of 24.6 and an SNR/Vvoxel of 0.18/mm3. 3D-radial images had an SNR of 8.5 and an SNR/Vvoxel of 0.02/mm3. FLORET resulted in an SNR of 15.5 and an SNR/Vvoxel of 0.36/mm3. The reported SNRs are without additional post-processing corrections, which would result in improved image quality for the UTE sequences.
Discussion
FLORET acquired higher resolution xenon ventilation images when compared to traditional GRE and 3D-radial sequences. When accounting for voxel volume, FLORET outperformed both GRE and 3D-radial with respect to SNR. Additionally, FLORET benefits from acquiring k0 in every projection, allowing for future corrections such as B1 inhomogeneity and magnetization decay.Conclusion
Highly-efficient UTE MRI spiral sequences allow for higher resolution, isotropic, fully-sampled xenon ventilation images. FLORET’s fewer excitations allows for higher flip angles and normalized SNR over GRE and 3D-radial images. Sampling k0 each projection permits image corrections and improvements. For a given magnetic moment and breath-hold, 3D-spiral ventilation imaging would permit detection of smaller ventilation defects, smaller changes in ventilation, shorter breath-hold durations, and/or time-resolved ventilation – advantages which are particularly crucial when implementing in pediatrics, where patients’ anatomy is small and breath-hold compliance is lower.
Acknowledgements
The authors thank the following sources for research funding and support: NIH R01 HL131012 and NIH R44 HL123299. Additionally, the authors would like to thank Ashley G. Anderson III PhD (Philips Healthcare) for the ability to implement the off resonance focusing code they developed.References
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