Bayesian algorithm using spatial priors for multiexponential T2 relaxometry from multiecho spin echo MRI
Article first published online: 20 JAN 2012
Copyright © 2012 Wiley Periodicals, Inc.
Magnetic Resonance in Medicine
Volume 68, Issue 5, pages 1536–1543, November 2012
How to Cite
Kumar, D., Nguyen, T. D., Gauthier, S. A. and Raj, A. (2012), Bayesian algorithm using spatial priors for multiexponential T2 relaxometry from multiecho spin echo MRI. Magn Reson Med, 68: 1536–1543. doi: 10.1002/mrm.24170
- Issue published online: 22 OCT 2012
- Article first published online: 20 JAN 2012
- Manuscript Accepted: 21 DEC 2011
- Manuscript Revised: 29 NOV 2011
- Manuscript Received: 21 JUN 2011
- T2 relaxometry;
- myelin water fraction;
- spatial priors
Multiexponential T2 relaxometry is a powerful research tool for detecting brain structural changes due to demyelinating diseases such as multiple sclerosis. However, because of unusually high signal-to-noise ratio requirement compared with other MR modalities and ill-posedness of the underlying inverse problem, the T2 distributions obtained with conventional approaches are frequently prone to noise effects. In this article, a novel multivoxel Bayesian algorithm using spatial prior information is proposed. This prior takes into account the expectation that volume fractions and T2 relaxation times of tissue compartments change smoothly within coherent brain regions. Three-dimensional multiecho spin echo MRI data were collected from five healthy volunteers at 1.5 T and myelin water fraction maps were obtained using the conventional and proposed algorithms. Compared with the conventional method, the proposed method provides myelin water fraction maps with improved depiction of brain structures and significantly lower coefficients of variance in white matter. Magn Reson Med, 2012. © 2012 Wiley Periodicals, Inc.