Spatial regularization of two-step MR velocity data sets significantly reduces velocity noise and provides image quality comparable to three-step data sets without regularization.
Enables shorter two-step MR velocity acquisitions; extends technical methods but leaves open clinical validation.
A technique dedicated to spatial regularization of magnetic resonance (MR) velocity data has been implemented to improve flow image quality. It is assumed that neighboring flow-velocity pixels are partially correlated, although large-velocity discontinuities remain possible. Increasing MR signal magnitude due to the in-flow effect also is used to enhance further reliability of the estimated velocity. By using an eight-step Fourier-encoding approach, 162 "reference" velocity images acquired in the ascending aorta from six healthy volunteers were compared with "raw" and "regularized" images that were computed from only two gradient steps. The mean square error decreased from 0.12 m(2) x s(-2) to 0.06 m(2) x s(-2) (P < 10-9) for velocity pixel values and from 1929 ml(2) x s(-2) to 1336 ml(2) x s(-2) (P < 0.01) for instantaneous flow rates. The regularization of two-step data sets provides the same velocity image quality as that found after using three-step data sets without regularization. The method can be applied to phase-velocity data sets of any MR technique to reduce velocity noise. J. Magn. Reson. Imaging 1999;10:851-860.
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Herment et al. (1999) studied this question.
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