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Comparison of three surrogate-based respiratory motion correction methods for 3D high resolution cardiac MRI
Juliane Ludwig1, Peter Speier2, Frank Seifert1, Tobias Schaeffter1,3, and Christoph Kolbitsch1,3

1Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany, 2Siemens Healthcare, Erlangen, Germany, 3King's College London, Division of Imaging Sciences and Biomedical Engineering, London, United Kingdom

Synopsis

Respiratory motion correction has been proposed to improve scan efficiency and ensure high image quality for 3D cardiac MRI. Nevertheless, these techniques often require dedicated data acquisition and cannot necessarily capture intra-cycle variations of the breathing. Here we compare three different surrogate signals (“pilot tone”, respiratory belt and MR-navigator) for a surrogate-based motion correction approach which provides motion information with high temporal resolution and can be combined with a wide range of different MR acquisition schemes. The temporal stability of these surrogates is assessed and motion correction of a 3D cardiac MR scan is demonstrated.

Introduction

When acquiring 3D high-resolution cardiac MR-data, respiratory motion can lead to strong motion artefacts and impair the quality of reconstructed images. Commonly, respiratory gating techniques are used to minimize respiratory motion artefacts but they suffer from low scan efficiency.1-2 Respiratory motion correction approaches have been proposed to overcome this problem.3-6 Nevertheless, they often require dedicated data acquisition and cannot necessarily capture intra-cycle variations of the breathing. Here we present an approach that uses motion-surrogates to obtain motion correction information with high temporal resolution. A short pre-scan is used to calibrate the surrogate signals to the respiratory motion of the heart. For the subsequent 3D-data acquisition the surrogate is then used for motion-correction (Fig 1). A comparison of three different surrogate signals (“pilot tone”7, respiratory belt and MR-navigator) is carried out and the results of motion correction are presented.

Methods

An overview of the calibration and motion correction method is given in Figure 1.

Pilot Tone: A pilot tone (PT) signal was created by a prototype set-up: The signal was generated by a commercial synthesizer (Hewlett Packard) connected to an additional inhouse-built non-resonant coil fixed to the bore of the scanner. The frequency was set such that the signal was recorded in the two-fold oversampled readout signal of the MR-data. During respiration the intensity of the received PT signal varied, which provided a continuous motion surrogate for each readout.

Respiratory Belt (RB): Two respiratory belt transducers (Biopac Systems, Inc) were fixed to the subjects around the chest and abdomen. The change of circumference of the body during the breathing cycle was measured with an internal air pressure system.

MR-navigator: This commonly used MR-navigator was obtained by tracking the motion of the dome of the right hemi-diaphragm. The motion of the diaphragm relates closely to the motion of the heart.2

Calibration scan: Cardiac, ECG-triggered, dynamic measurements were performed at 3T (MAGNETOM Verio, Siemens Healthcare, Germany) on 3 volunteers (2 female, age 30 ± 2 years). For each cardiac cycle a coronal and sagittal 2D-image were acquired to capture the 3D-motion of the heart with an inhouse-modified FLASH sequence, TE=1.4ms, TR=2.4ms, FOV=300x300mm2 and voxel size=1.56x1.56x8mm3. The calibration scan was carried out for 60s.

Registration + Linear correlation: To determine translation parameters in foot-head (FH), anterior-posterior (AP) and right-left (RL) plane, a region of interest around the heart was chosen manually for both coronal and sagittal view. A normalized cross-correlation function was used to determine the translational breathing motion of the heart in 3D. The surrogate signals were then calibrated to the determined translation using a linear model.

Assessment of temporal stability: To assess the temporal stability of the surrogate signals, the same scan used for calibration was carried out for additional 130s. The motion predictions of the surrogate signals based on the 60s calibration were then compared to the heart motion determined during these additional 130s.

3D high-resolution cardiac scan: A 3D FLASH cardiac-triggered scan with TE=4.1ms, TR=7.3ms, flip angle=12°, FOV=300x244x32mm3 and voxel size=1.56x1.56x2mm3 was obtained during free-breathing. A MR-navigator was obtained for each cardiac cycle but was not used for gating.

Surrogate-based motion correction: Based on the calibration step before, the heart motion for each readout was calculated using the surrogate signals. Motion correction was done prior to offline image reconstruction with Matlab by applying a phase shift to the k-space data, using all MR-raw-data.


Results and Discussion

The temporal stability of the surrogate signals is depicted in Figure 2 in steps of 10s for one volunteer. As expected the MR-navigator shows the best temporal stability but PT and RB also show good temporal behavior. Figure 3 shows an overlay of the different surrogate signals compared to the FH-heart motion estimated from the calibration scan. Very good agreement between all surrogate signals can be seen. Based on this calibration scan, regression curves have been derived with the respective correlation coefficients R2Nav=0.95, R2PT=0.79, R2RS=0.75 as displayed in Figure 4. Figure 5 shows reformatted images showing the coronary arteries for the different motion-correction approaches. Motion correction using the MR-navigator and pilot tone improved visualization of the coronary arteries. Unsuccessful motion correction using the respiratory belt may be due to inaccurate temporal synchronization.

Conclusion

We have compared the correlation between MR-navigator, PT, RB and the registered cardiac motion due to breathing and we have demonstrated the feasibility to use these surrogate signals for motion correction with high temporal resolution. PT and RB are independent of the MR-data acquisition and can therefore be combined with any MR-scan, making this a very flexible motion-correction approach.

Acknowledgements

No acknowledgement found.

References

1Scott A D, Keegan J, Firmin, David N. Motion in Cardiovascular MR Imaging. Radiology: Volume 250: Number 2 – February 2009.

2McClelland J R, Hawkes D J, Schaeffter T, King A P. Respiratory motion models: A review. Medical Image Analysis 17, p. 19-42, 2013.

3Aitken A P, Henningsson M, Botnar RM, Schaeffter T, Prieto C. 100% Efficient three-dimensional coronary MR angiography with two-dimensional beat-to-beat translational and bin-to-bin affine motion correction. Magn Reson Med. 2015;74:756–764.

4Luo J, Addy N O, Ingle R R, et al. Nonrigid Motion Correction With 3D Image-Based Navigators for Coronary MR Angiography. Magn Reson Med. 2017;77:1884–1893.

5Schmidt J F M, Buehrer M, Boesiger P, Kozerke S. Nonrigid retrospective respiratory motion correction in whole-heart coronary MRA. Magn Reson Med. 2011;66:1541–1549.

6Bhat H, Ge L, Nielles-Vallespin S, Zuehlsdorff S, Li D. 3D radial sampling and 3D affine transform-based respiratory motion correction technique for free-breathing whole-heart coronary MRA with 100% imaging efficiency. Magn Reson Med. 2011;65:1269–1277.

7Speier S, et al. PT-Nav: A Novel Respiratory Navigation Method for Continuous Acquisition Based on Modulation of a Pilot Tone in the MR-Receiver. ESMRMB 129:97-98, 2015. Doi: 10.1007/s10334-015-0487-2.

Figures

Figure 1: Overview of proposed two-step method. First, parallel acquisition of MR data and the surrogate data is done for about 60s to calibrate the surrogate signals to the respiratory motion of the heart and derive a motion model. The data of subsequent 3D scans can then be motion corrected using the motion model and the respective surrogate data.

Figure 2: Temporal stability of the surrogate. The first 60s have been used to calibrate the surrogate signals to the respiratory heart motion. Using the motion model the heart motion for the next 130s was then predicted in steps of 10s and compared to the registered heart motion. The mean errors are displayed. The MR-navigator shows the best temporal stability, followed by the pilot tone and the respiratory belt.

Figure 3: Overlay of the surrogate signals (pilot tone, respiratory belt and MR-navigator) and the registered FH-heart motion from the calibration scan. All signals lie in very good agreement with the heart motion.

Figure 4: Regression curves for the three surrogate signals (pilot tone, respiratory belt and MR-navigator. The best correlation has been found for the MR-navigator but also the pilot tone and the respiratory belt are well suited for predicting the heart motion.

Figure 5: Reformatted images for the three different motion correction approaches. The MR-navigator suits best for motion correction as expected. The coronary arteries become better visible also for the pilot tone. The motion correction for the respiratory belt does not lead to good results.

Proc. Intl. Soc. Mag. Reson. Med. 26 (2018)
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