An Iterative Approach to Respiratory Self-Navigation Allows for Improved Image Quality and 100% Scan Efficiency in Contrast-Enhanced Inversion-Recovery Whole-Heart Coronary MRA at 3T; a First Patient Study
Giulia Ginami1, Davide Piccini1,2, Pierre Monney3, Pier Giorgio Masci3, and Matthias Stuber1,4

1University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, 2Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland, 3Division of Cardiology and Cardiac MR Center, University Hospital of Lausanne (CHUV), Lausanne, Switzerland, 4Center for Biomedical Imaging (CIBM), Lausanne, Switzerland

Synopsis

The performance of Self-Navigation (SN) for respiratory motion compensation in 3T whole-heart coronary MRA may be compromised by contrast variations secondary to slow-infusion of a contrast agent. In this study, we quantitatively and successfully tested the hypothesis that an Iterative approach to SN (IT-SN) leads to improved performance during slow infusion.

Introduction

The use of 3D whole-heart coronary MRA at 3T is still limited as whole-heart SSFP acquisitions remain challenging. To overcome that hurdle, a slow-infusion Gd injection in conjunction with a gradient-echo readout has been proposed (1) and successfully applied (2,3). To enable free-breathing acquisition, these methods make use of a diaphragmatic navigator (NAV) (4). Respiratory self-navigation (SN) has recently been introduced (5,6) as a promising alternative with respect to NAV; it enables the extraction of respiratory motion information from the imaging data directly, provides 100% scan efficiency, and alleviates the need of sophisticated plan scanning. Typically, a superior-inferior (SI) projection is acquired at the very beginning of each data segment (Figure 1a). One of these SI projections is then taken as reference, and all the other SI projections are compared to that reference in order to estimate and compensate for respiratory motion. The use of slow infusion throughout data acquisition, however, introduces transient signal variations between the reference profile and the subsequently acquired SI projections (Figure 1b). This may adversely affect both the extraction of SI displacement measurements and the efficacy of respiratory motion compensation. A recently introduced iterative approach to SN (IT-SN) operates by iteratively minimizing residual respiratory motion throughout an SI projection series and, thus, without requiring a specific SI projection as a reference profile (7). Here, we tested the hypothesis that IT-SN can provide 100% scan efficiency and improved image quality with respect to standard SN in whole-heart coronary MRA at 3T during slow-infusion.

Methods

Data acquisition was performed in N=8 patients on a clinical 3T Scanner (Siemens Magnetom, Skyra) using a prototype 3D radial trajectory (8) specifically adapted for performing respiratory SN (Figure 1a). Data acquisition was performed during slow-infusion (Gadovist, 0.03 ml/sec, 0.1 ml/kg). Imaging parameters for the ECG-triggered, fat-saturated, GRE sequence were as follows: FoV (220mm)3, voxel size (1.15mm)3, radiofrequency excitation angle 15°, TE 2.9ms, TR 4.8ms, bandwidth 1002 Hz/pixel. For each data segment, 15-35 radial lines were acquired, over 377-800 heart-beats (~ 12’000 radial lines in total). Inversion recovery preparation was used (TI 290ms). First, the acquired data were reconstructed by using the standard (reference-based) SN and the first SI projection acquired at end expiration was used as the reference profile (9). Secondly, data were motion corrected and reconstructed using IT-SN. Finally, data were also reconstructed without any respiratory motion correction for comparison. Reconstructed datasets were analyzed by using the software tool described in (10); percentage vessel sharpness (%VS) and visible vessel length were computed along multiple coronary segments. Statistical significances were assessed using Bonferroni correction for multiple comparisons.

Results

Data acquisition amounted to ≈7 min for every subject, with 100% scan efficiency. All the quantified endpoints are summarized in Table 1. An improvement in coronary delineation is not only observed between uncorrected and corrected datasets (white arrows in Figure 2), but also when IT-SN corrected datasets are compared with datasets corrected by using standard SN (blue arrows in Figure 2). Furthermore, transient signal and contrast variations among the SI projections were observed during slow infusion (Figure 1a, Figure 3a, 3d) and led to failure of the conventional SN algorithm to identify and adequately correct for respiratory displacement of the heart. However, IT-SN remained successful in all cases and a significantly improved visible vessel length and %VS was observed for most coronary segments as compared to SN or non-corrected data. These findings are corroborated by the coronary MRA displayed in Figures 2 & 3.

Discussion and Conclusion

We successfully demonstrated that IT-SN enables self-navigated whole-heart coronary MRA acquisitions during slow infusion of a contrast agent at 3T. As such, indirect estimation of heart motion and sophisticated sequence planning can be avoided; furthermore, 100% scan efficiency is enabled even in the presence of slow-infusion. Simultaneously, and due to the fact that the choice of a specific reference SI projection is no longer needed, both motion detection and the accuracy of the thus related correction may be less affected by transient signal and contrast changes of the SI projections. Preliminary results demonstrate that IT-SN improves image quality with respect to standard SN in the presence of slow infusion at 3T. Studies in larger patient cohorts and in comparison to the gold standard x-ray coronary angiography are now warranted.

Acknowledgements

This work was supported by the Swiss National Science Foundation grants 320030_143923 and 326030_150828.

References

(1) Bi X, Carr JC, Li D. Whole-heart coronary magnetic resonance angiography at 3 Tesla in 5 minutes with slow infusion of Gd-BOPTA, a high-relaxivity clinical contrast agent. Magnetic resonance in medicine 2007;58(1):1-7.

(2) Yang Q, Li K, Liu X, Bi X, Liu Z, An J, Zhang A, Jerecic R, Li D. Contrast-enhanced whole-heart coronary magnetic resonance angiography at 3.0-T: a comparative study with X-ray angiography in a single center. Journal of the American College of Cardiology 2009;54(1):69-76.

(3) Yang Q, Li K, Liu X, Du X, Bi X, Huang F, Jerecic R, Liu Z, An J, Xu D, Zheng H, Fan Z, Li D. 3.0T whole-heart coronary magnetic resonance angiography performed with 32-channel cardiac coils: a single-center experience. Circulation Cardiovascular imaging 2012;5(5):573-579.

(4) Stuber M, Botnar RM, Danias PG, Kissinger KV, Manning WJ. Submillimeter three-dimensional coronary MR angiography with real-time navigator correction: comparison of navigator locations. Radiology 1999;212(2):579-587.

(5) Stehning C, Bornert P, Nehrke K, Eggers H, Stuber M. Free-breathing whole-heart coronary MRA with 3D radial SSFP and self-navigated image reconstruction. Magnetic resonance in medicine 2005;54(2):476-480.

(6) Piccini D, Littmann A, Nielles-Vallespin S, Zenge MO. Respiratory self-navigation for whole-heart bright-blood coronary MRI: methods for robust isolation and automatic segmentation of the blood pool. Magnetic resonance in medicine 2012;68(2):571-579.

(7) Ginami G, Bonanno G, Schwitter J, Stuber M, Piccini D. An iterative approach to respiratory self-navigated whole-heart coronary MRA significantly improves image quality in a preliminary patient study. Magnetic resonance in medicine 2015. doi: 10.1002/mrm.25761

(8) Piccini D, Littmann A, Nielles-Vallespin S, Zenge MO. Spiral phyllotaxis: the natural way to construct a 3D radial trajectory in MRI. Magnetic resonance in medicine 2011;66(4):1049-1056.

(9) Piccini D, Bonanno G, Ginami G, Littmann A, Zenge MO, Stuber M. Is there an optimal respiratory reference position for self-navigated whole-heart coronary MR angiography? Journal of magnetic resonance imaging : JMRI 2015. doi: 10.1002/jmri.24992

(10) Etienne A, Botnar RM, Van Muiswinkel AM, Boesiger P, Manning WJ, Stuber M. "Soap-Bubble" visualization and quantitative analysis of 3D coronary magnetic resonance angiograms. Magnetic resonance in medicine 2002;48(4):658-666.

Figures

Figure 1: Acquisition scheme. Data acquisition is performed with GRE that is preceded by an inversion pulse (a), and during slow infusion. Signal and contrast variations can be observed throughout the whole series of collected SI projections (b) due to transient changes in contrast agent concentration.

Figure2: Multiplanar reformats from two patients. Improvement in image quality (white arrows) can be observed between uncorrected (a, d) and corrected datasets (b,c, e,f). Furthermore (blue arrows), an improvement can be visually appreciated when IT-SN corrected datasets (c, f) are compared with datasets corrected by using the standard SN (b,e).

Figure3: Respiratory motion detection provided by standard SN (a, red line) and IT-SN (d, green line). Signal variations of the SI projections (b,e) post contrast affect motion estimation by standard SN (drift of respiratory signal). IT-SN is less affected by these changes and leads to an improved image quality (c,f).

Table1:Quantitative results. All the computed endpoints quantifying coronary delineation confirm an improvement in vessel conspicuity when IT-SN is used (with respect to both standard SN and Uncorrected datasets). (*) Indicates statistical significance with respect to standard SN, whereas (ƚ) refers to significance relative to the uncorrected datasets (P<0.05, Bonferroni corrected).



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