Retrospective self-gated 3D UTE MRI in the mouse lung
Jinbang Guo1,2, Xuefeng Cao1,3, Zackary I. Cleveland1, and Jason C. Woods1,2

1Center for Pulmonary Imaging Research, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States, 2Physics, Washington University in St. Louis, St. Louis, MO, United States, 3Department of Physics, University of Cincinnati, Cincinnati, OH, United States

Synopsis

Motion due to respiration is one of the major difficulties in lung imaging of mice, which have a 10-20-fold higher respiratory rate than humans. In this study, we demonstrate that the FID signal amplitude (k = 0) as a function of projection number in center-out radial 3D UTE reflects respiratory motion. Retrospective "self"-gating using this FID signal amplitude was applied to extract data for end-expiration and end-inspiration respectively. Quantitative analysis of tidal volumes and lung parenchymal signal match external measurements and physiological expectations.

Target audience

Researchers in the fields of lung imaging and ultrashort echo-time (UTE) imaging.

Purpose

Motion due to respiration is one of the major difficulties in lung imaging. This problem is particularly pronounced in mice, which have a 10-20-fold higher respiratory rate than humans. To compensate for respiratory motion in vivo, MR acquisitions are usually synchronized with the respiration cycle either using a ventilator or prospective respiratory gating. In many cases spontaneous breathing is advantageous to avoid ventilator-induced lung injury or for physiological measurement. Further, prospective gating errors result from abnormal respiration waveforms caused by body motion. These problems can be avoided by retrospective gating (i.e., binning data after acquisition to avoid periods of motion). In traditional Cartesian imaging, retrospective gating typically requires that specialized sequences be employed. However, the situation is different in center-out radial encoding because respiratory motion slightly alters the local field experienced by spins within the lung, providing a detectable signal from the initial point of free induction decay (FID). Thus, the signal amplitude of each FID (i.e., k = 0) can be used for retrospective "self"-gating. Here we demonstrate that this retrospective "self"-gating can be implemented in mice using 3D UTE.

Methods

All experiments were approved by Institutional Animal Care and Use Committee. Imaging was performed using a Bruker 7T scanner on 10 free-breathing 7-week old C57BL/6J mice. Mice were anesthetized with isoflurane and placed supine inside a quadrature birdcage coil (length: 50 mm, inner diameter: 35 mm). In addition, a pressure sensor of a small animal monitoring system (SA Instruments, Inc.) was taped on the mouse stomach to monitor the respiratory motion. Spherical k-space coverage was used for 3D UTE MRI with 2D golden means determining the azimuthal and polar angles of the endpoint of each radial spoke1. The RF excitation pulse was applied with a slab selection gradient to focus the field-of-view (FOV) on the lung, with data acquisition starting immediately when the readout gradient was ramped after a slab refocusing gradient. A linear phase increment of 117° × RF pulse number added to each RF pulse was combined with a negating readout gradient and a strong spoiler gradient for spoiling2. Total acquisition time was 12 minutes with TR = 7 ms, TE = 0.63 ms, FA = 5°, FOV = (30 mm)3, voxel = (0.23 mm)3, 64 points along each projection and 2-fold oversampling of projections. The respiration rate of one mouse was changed by adjusting isoflurane level to investigate the period of the FID signal amplitude as a function of projection number. FID signal amplitude as a function of projection number was smoothed by a moving-average filter and the resulting smoothed first- and second-order derivatives were combined to extract data at expiration and inspiration respectively, as shown in Fig. 2. The retrospective-gated radial data were resampled onto a Cartesian grid by convolving with a Kaiser-Bessel window3 before Fourier transform. Tidal volume was calculated by measuring the lung volume difference between the expiration and inspiration images. Lung parenchyma SNR was defined as the lung parenchyma signal divided by the standard deviation in the background.

Results and Discussion

FID signal amplitude as a function of projection number at 3 different monitored respiration rates (~110/min, 80/min, and 60/min) is shown in Fig. 1, with plateaus and troughs corresponding to expiration and inspiration respectively. The respiration rates estimated from the amplitude curves are 109/min, 75/min and 64/min respectively, consistent with external monitoring. Fig. 2 shows the projections extracted for expiration (49462 projections) and inspiration (9864 projections) marked by the red and blue lines respectively. The resulting coronal and sagittal images are shown in Fig. 3. The red lines emphasize the diaphragm displacement between expiration and inspiration. Lung volume measured at inspiration and expiration is 0.55 ml and 0.44 ml respectively, resulting in 0.11 ml of tidal volume, consistent with previous plethysmographic measurements in (non-anesthetized) C57BL/6J mice of 0.16 ml (range 0.13-0.21 ml)4. The lung parenchyma SNR at inspiration (11.2) is lower than that at expiration (21.2) because of bulk density decrease, motion artifacts, and projection undersampling. The expiration/inspiration signal-intensity ratio in lung parenchyma is 1.2, consistent with the inspiration/expiration lung-volume ratio of 1.25, assuming similar T2*.

Conclusion

We demonstrate the feasibility of retrospective-gated 3D UTE pulmonary MRI on small animals. The high parenchymal SNR in both expiration and inspiration images enables quantitative analysis of lung parenchyma and lung tidal volume, which match physiological expectations.

Acknowledgements

No acknowledgement found.

References

1. Chan RW, et al. Temporal stability of adaptive 3D radial MRI using multidimensional golden means. Magn Reson Med 2009;61(2):354-363. 2. Zur Y, et al. Spoiling of transverse magnetization in steady-state sequences. Magn Reson Med 1991;21(2):251-263. 3. Jackson JI, et al. Selection of a convolution function for Fourier inversion using gridding [computerised tomography application]. IEEE Transactions on Medical Imaging 1991;10(3):473-478. 4. Tankersley CG, et al. Genetic control of differential baseline breathing pattern. Journal of Applied Physiology 1997;82(3):874-881.

Figures

Figure 1: FID signal amplitude as a function of projection number at different respiration rates (~110/min, 80/min, and 60/min, read from small animal monitoring system). Troughs correspond to inspiration and the plateaus to expiration.

Figure 2: First- and second-order derivatives were combined to extract projections for expiration and inspiration, marked by red and blue lines respectively.

Figure 3: Example lung images reconstructed from data extracted at expiration and inspiration. The red lines manifest the relative diaphragm displacement between expiration and inspiration.



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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