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Updated: Jun 13, 2026

A Novel Application of Musculoskeletal Ultrasound Imaging
Published on: September 17, 2013
Determinants and propagation of velocity uncertainty in 2D phase-contrast MRI
Ana E Rodríguez-Soto1, Eleanor L Schuchardt2,3, Hari K Narayan2,3
1Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
Purpose:
To quantify the contributions of signal-to-noise ratio (SNR) and velocity-to-encoding ratio (v/VENC) to velocity uncertainty in phase-contrast (PC) MRI and to develop a framework for in vivo voxel-wise uncertainty estimation.
Methods:
Through-plane 2D PC-MRI of the ascending aorta was acquired using multiple velocity encodings (150, 200, 300 cm/s) and flip angles (0°, 5°, 15°, 20°) to vary v/VENC and SNR. Voxel-wise SNR and velocity uncertainty maps were generated using empirically calibrated phase-noise modeling. Phase-resolved subject-level analyses were performed to quantify the relative contributions of SNR and |v|/VENC to percent velocity uncertainty (%unc). Uncertainty was propagated to flow, stroke volume (SV), and cardiac output (CO).
Results:
Velocity uncertainty varied substantially across the cardiac cycle and depended on both SNR and |v|/VENC. Across cardiac phases, |v|/VENC accounted for most explained variance in %unc (partial R2=0.666), while SNR provided a smaller but meaningful contribution (partial R2=0.287; full R2=0.909). Near peak systole, SNR contributed more strongly while overall uncertainty remained low. In contrast, diastolic %unc became unstable as velocity approached zero. These effects were most pronounced at low |v|/VENC, where higher VENC settings increased uncertainty despite similar SNR. SV uncertainty ranged from 0.27% to 1.07% across VENC×FA protocols.
Conclusion:
Velocity uncertainty in PC-MRI depends on both SNR and VENC adequacy in a physiologically phase-dependent manner. Relative uncertainty may become inadequate for precise quantification in low-flow applications, such as diastolic regurgitant jets, despite adequate SNR. Spatiotemporal uncertainty mapping provides a framework for uncertainty-aware PC-MRI acquisition and interpretation.
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