title: Utilizing the diffusion-to-noise ratio to optimize magnetic resonance diffusion tensor acquisition strategies for improving measurements of diffusion anisotropy.
abstract: It is well known that quantitative anisotropy measurements derived from the diffusion tensor are extremely sensitive to noise contamination. The level of noise in the diffusion tensor imaging (DTI) experiment is usually measured from some estimate of the signal-to-noise ratio (SNR) in the component diffusion-weighted (DW) images. This measure is, however, highly dependent on experimental parameters, such as the diffusion attenuation b-value and the diffusion coefficient of the subject. Conversely, the diffusion-to-noise ratio (DNR), defined as the SNR of the calculated diffusion tensor trace map, provides a reliable estimate of noise contamination, which is largely independent of such parameters. In this work it is demonstrated how reliable anisotropy measurements can be obtained using an image acquisition strategy that optimizes the DNR of the DTI experiment. This acquisition scheme is shown to provide noise-independent measurements of typical diffusion anisotropy values found in the human brain.
authors.affiliation: Department of Engineering Science, University of Oxford, Parks Road, Oxford, England. paa@robots.ox.ac.uk
authors.forename: P A
authors.initials: PA
authors.lastname: Armitage
authors.forename: M E
authors.initials: ME
authors.lastname: Bastin
mesh_terms: D016880:Anisotropy; D016477:Artifacts; D001921:Brain / Q000033:anatomy & histology*; D004058:Diffusion; D006801:Humans; D007089:Image Enhancement; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D019047:Phantoms, Imaging; D012016:Reference Values; D015203:Reproducibility of Results