Rapid microscopic fractional anisotropy imaging via an optimized linear regression formulation

Water diffusion anisotropy in the human brain is affected by disease, trauma, and development. Microscopic fractional (?FA) a MRI (dMRI) metric that can quantify water independent of neuron fiber orientation dispersion. However, there are several different techniques to estimate ?FA few have demonstrated full imaging capabilities within clinically viable scan times resolutions. Here, we present an optimized spherical tensor encoding (STE) technique acquire directly from 2nd order cumulant expansion powder averaged dMRI signal obtained direct linear regression (i.e. kurtosis) which requires fewer powder-averaged signals than other STE fitting be rapidly computed. We found optimal parameters for white matter were maximum b-value 2000 s/mm2 ratio LTE encoded acquisitions 1.7 our system specifications. then compared two implementations approach well-established gamma model 4 healthy volunteers on 3 Tesla system. One implementation used mean diffusivity (D) fit expansion, while estimation D low b-values. Both showed strong correlations with (? = 0.97 ? 0.90) but biases ?0.11 ? 0.02 relative also observed, respectively. All three measurements good test-retest reliability ? 0.79 bias 0). To demonstrate potential time advantage approach, 2 mm isotropic resolution was over 10 cm slab using subsampled data set would correspond 3.3-min scan. Accordingly, results introduce optimization procedure has enabled nearly only minutes.