A fully automatic reference deconvolution strategy to increase the accuracy of in vivo lipid signal quantification.

Abstract

Lipid signals measured by (1)H MR spectroscopy cannot be adequately quantified by common fitting routines like VARPRO or AMARES, if lipid spectra are distorted by irregular spatial and temporal inhomogeneities of the static magnetic field during readout. A fully automatic reference deconvolution algorithm is presented that eliminates these distortions before application of fitting routines. The measured signal of the dominant methyl resonance is isolated with aid of a spectral estimator (estimation of parameters via rotational invariance techniques) and used as reference signal for estimation of distortions. A Wiener filter is applied to deconvolve those distortions in the lipid spectrum. Performance of the algorithm is assessed for different bandwidths and shapes of distortions, using artificially distorted as well as measured data. Application of the fully automatic reference deconvolution algorithm on simulated spectra yields a distinct increase in quantification accuracy. Deconvolved in vivo spectra of subcutaneous fat indicate reduced spectral overlap after application of the proposed strategy. The proposed method is helpful for in vivo magnetic resonance spectroscopy of adipose tissue to correct for effects of field inhomogeneities within the voxel and for inevitable eddy current effects. Quantification accuracy is improved by eliminating distortions before application of fitting routines.