Improved initial value estimation for short echo time magnetic resonance spectroscopy spectral analysis using short T2 signal attenuation

Abstract

Robust spectral analysis of magnetic resonance spectroscopy data frequently uses a spectral model with prior metabolite signal information within a nonlinear least squares optimization algorithm. Starting values for the spectral model greatly influence the final results. Short echo time magnetic resonance spectroscopy contains broad signals that overlap with metabolite signals, complicating the estimation of starting values. We describe a method for more robust initial value estimation using a filter to attenuate short T(2) signal contributions (e.g., macromolecules or residual lipids). The method attenuates signals by truncating early points in the data set. Metabolite peak estimation is simplified by the removal of broad, short T(2) signals, and corrections for metabolite signal truncation are described. Short echo time simulated Monte Carlo data and in vivo data were used to validate the method. Areas for metabolite signals in the Monte Carlo data with singlet (N-acetylaspartate, creatine, choline) and singlet-like (myo-inositol) resonances were estimated within 10% of actual value for various metabolite line widths, signal-to-noise ratios, and underlying broad signal contributions. Initial value estimates of in vivo magnetic resonance spectroscopy data were within 14% of metabolite area ratios relative to the creatine peak fitted using established magnetic resonance spectroscopy spectral analysis software.