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Quantitative comparison between Multislice 2D Breath-hold Cartesian and Free-breathing Anisotropic FOV 3D Golden Angle Radial Stack-of-Stars for functional cardiac MRI
Joao Tourais1,2, Guruprasad Krishnamoorthy1,2, Marc Kouwenhoven1, Jouke Smink1, and Marcel Breeuwer1,2

1Division MR Clinical Science, Philips, Best, Netherlands, 2Dept. of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands

Synopsis

Radial trajectories are ideal in dynamic imaging due to its robustness to flow and motion. Multislice 2D Breath-hold Cartesian acquisition is still the most used approach to acquire functional cardiac MRI. In this work, we demonstrate the feasibility of Free-breathing 3D Radial stack-of-stars imaging with in-plane anisotropic FOV. The prosed approach can reduce imaging times in acquisitions where the object dimensions are anisotropic, while still enabling a reliable Ejection Fraction estimation.

Background

Radial trajectories are ideal in dynamic imaging due to their favorable properties: robustness to flow and motion1, diffuse aliasing patterns, and reduced sensitivity to undersampling2. While conventional 3D golden angle radial stack-of-stars (3D GA-SOS) allows anisotropy of the field-of-view (FOV) in the slice direction (Volume thickness), it does not support in-plane anisotropic FOV. This can lead to sub-optimal sampling and/or unnecessary long scan time when the object being imaged has anisotropic in-plane dimensions (e.g. axial scans of the abdomen, chest, etc.). Previously3, the feasibility of in-plane anisotropic FOV for 3D GA-SOS was demonstrated in abdominal MRI by acquiring an optimal sampling which matches the anatomy of the body, in comparison with the conventional 3D GA-SOS. The purpose of this work is to assess the impact of anisotropic in-plane FOV for 3D GA-SOS regarding the cardiac function evaluation.

Methods

In conventional 3D GA-SOS, the radial angles have a uniform angular distribution because the consecutively acquired spokes are equally spaced (i.e. golden angle = 111.2°). As shown previously3,4, a radial anisotropic FOV (θanisotropic(n)) can be computed for GA-SOS, where θ(i) of the ith GA spoke was computed as θ(i)=θfull [A(i)]+D(i)*∆θanisotropic[A(i)], with A(i)=floor[indexga(i)], D(i)=goldenratio(i)-A(i). In the case of 3D GA-SOS, the computed radial angular distribution was repeated for every phase encoding step in the slice direction.

The proposed anisotropic FOV sampling scheme was implemented on a Philips Ingenia 1.5T MR scanner. Multislice 2D (M2D) Cartesian Breath-hold (BH) and 3D Respiratory belt gated GA-SOS Free-breathing (FB) short-axis views of the left ventricle were acquired using balanced SSFP in 7 volunteers (65±7 years, 6 males). The 3D GA-SOS was acquired with isotropic and anisotropic FOV. The imaging parameters are listed in Figure 1. The k-space sampling pattern generation and the image reconstruction were performed inline on the scanner. The dedicated sampling density compensation factor was calculated and taken into account during the reconstruction. Left Ventricle segmentation and Ejection Fraction estimation were performed on a dedicated workstation (Philips Intellispace Portal Cardiac Analysis software).

Results

Figure 2 compares the 3 techniques evaluated in this study. As expected, the M2D Cartesian BH acquisition provides better myocardium-blood contrast due to the fresh-blood in-flow effect. In the 3D acquisitions, the myocardium-blood contrast is reduced but is still sufficient for myocardial segmentation. The image quality of the 3D acquisitions obtained using anisotropic FOV is comparable with the isotropic FOV, despite the shorter scan time (in the order of 25-35%, related to the chosen anisotropy ratio) for the anisotropic FOV approach. Including the necessary breath-hold recovery, the M2D scans have a longer scan time than the respiratory-gated 3D scans and are less convenient for the patient due to the multiple breath-holds. Figure 3 shows the comparison of Ejection Fraction for both 3D radial acquisitions versus the M2D Cartesian acquisition. A higher correlation (R2=0.92 vs R2=0.89) is observed in the Anisotropic FOV case. The Bland-Altman analysis shows good agreement between the two 3D GA-SOS approaches against the Cartesian approach.

Conclusion

We demonstrate the feasibility of Free-breathing 3D Radial stack-of-stars imaging with in-plane anisotropic FOV, which can reduce imaging times (in the order of 25-35%) in acquisitions where the object dimensions are anisotropic, and showing good correlation for Ejection Fraction with the conventional M2D Cartesian acquisition.

Acknowledgements

This work was supported by the European Commission within the Horizon 2020 Framework through the MSCA-ITN-ETN European Training Networks (project number 642458).

References

  1. Nishimura, D. G., Jackson, J. I. and Pauly, J. M. (1991), On the nature and reduction of the displacement artifact in flow images. Magn. Reson. Med., 22: 481–492. doi:10.1002/mrm.1910220255,
  2. Glover, G. H. and Pauly, J. M. (1992), Projection Reconstruction Techniques for Reduction of Motion Effects in MRI. Magn. Reson. Med., 28: 275–289. doi:10.1002/mrm.1910280209,
  3. Tourais, J., Krishnamoorthy, G., Kouwenhoven, M., Smink, J., Breeuwer, M. (2018) 3D Golden Angle Stack-of-Stars with Anisotropic Field-of-View. In Proceedings ISMRM-ESMRMB 2018,
  4. Larson PEZ, Gurney PT, Nishimura DG. "Anisotropic Field-of-Views in Radial Imaging." IEEE Transactions on Medical Imaging2008; 27(1): 47-57.

Figures

Figure1. Imaging parameters. M2D: Multislice 2D; BH: Breath-hold; FOV: Field-of-View; GA-SOS: Golden Angle Stack-of-Stars

Figure 2. Comparison between the Multislice 2D Cartesian Breath-hold scans (M2D Cartesian), 3D Radial Golden Angle Stack-of-Stars Free-breathing scans (3D Isotropic FOV Radial SOS) and 3D Golden Angle Anisotropic In-plane Field-of-View Stack-of-Stars (3D Anisotropic FOV Radial SOS).

Figure 3. Comparison of Ejection Fraction for both 3D Radial approaches (In-plane Isotropic FOV and Anisotropic FOV) versus the M2D Cartesian Breath-hold acquisition. Top: Regression plot; Bottom Left: Bland-Altman analysis between Isotropic FOV 3D GA-SOS and M2D Cartesian BH; Bottom Right: Bland-Altman analysis between Anisotropic FOV 3D GA-SOS and M2D Cartesian BH.

Proc. Intl. Soc. Mag. Reson. Med. 27 (2019)
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