Numerical and experimental study of a novel phase contrast magnetic resonance (PC-MR) imaging technique: sparse interleaved referencing PC-MR imaging.
OBJECTIVE
To use numerical simulation and experimental approaches to introduce a novel phase contrast magnetic resonance (PC-MR) data processing technique termed Sparse Interleaved Referencing PC-MR, with potential to improve accuracy, temporal resolution, and signal-to-noise ratio (SNR) of PC-MR data.


METHODS
Computational fluid dynamics data were generated for a two-chamber orifice flow model simulating valvular regurgitation. The numerical results were validated and used to simulate conventional and Sparse Interleaved Referencing PC-MR data acquisitions. Common data sets were processed using conventional and Sparse Interleaved Referencing approaches and quantitative errors in velocity-time waveforms were measured and compared. In vitro phantom jet flow data and in vivo ascending aorta data were acquired and used to simulate Sparse Interleaved Referencing PC-MR.


RESULTS
The Sparse Interleaved Referencing PC-MR data showed significantly better representation of the velocity-time waveform in three areas: (i) lower root-mean-square errors (9.0 +/- 1.0% versus 24.0 +/- 0.2%; P < 0.005), (ii) simulation of conventionally processed data showed a pattern of peak velocity overestimation, which was experimentally demonstrated in in vitro data, whereas overestimation of peak velocity was dramatically attenuated using Sparse Interleaved Referencing (2.8 +/- 0.4% versus 16.9 +/- 6.4%, P < 0.005), and (iii) compared with the conventional scan, an average of 119.4 +/- 26.6% (P < 0.005) SNR was realized in in vitro and in vivo Sparse Interleaved Referencing PC-MR data.


CONCLUSIONS
Simulation and in vitro/in vivo results show that Sparse Interleaved Referencing PC-MR processed data in pulsatile and jet flow showed higher accuracy, better peak velocity representation, and improved SNR compared with the data processed using the conventional PC-MR method.
Li
Longchuan
L
Biomedical Imaging Technology Center, Emory University, Atlanta, Georgia, USA.
Doyle
Mark
M
Rayarao
Geetha
G
Biederman
Robert W W
RW
Anayiotos
Andreas
A
D001021:Aortic Valve; D001024:Aortic Valve Stenosis / Q000503:physiopathology; D001783:Blood Flow Velocity; D003198:Computer Simulation; D003287:Contrast Media; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D019047:Phantoms, Imaging
D003287:Contrast Media