Frequency-selective quantification of short-echo time Magnetic Resonance spectra
ABSTRACT Short-echo time magnetic resonance (MR) spectra contain large nuisance components which should be removed in order to improve quantification of the underlying metabolite concentrations. This paper shows that powerful filtering techniques such as the maximum-phase FIR filter or HLSVD-PRO proposed by Sundin et al. and Laudadio et al., respectively, as used in long-echo time MR spectral quantification, can be applied to their more complex short-echo time spectral counterparts. Both filters are extensively studied in the presence of various unwanted components. In most of the cases the maximum-phase FIR filter outperforms HLSVD-PRO. The potential and limitations of both filters are reported
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ABSTRACT: Reliable quantification of the macromolecule signals in short echo-time H-1 MRS spectra is particularly important at high magnetic fields for an accurate quantification of metabolite concentrations (the neurochemical profile) due to effectively increased spectral resolution of the macromolecule components. The purpose of the present study was to assess two approaches of quantification, which take the contribution of macromolecules into account in the quantification step. H-1 spectra were acquired on a 14.1 T/26 cm horizontal scanner on five rats using the ultra-short echo-time SPECIAL (spin echo full intensity acquired localization) spectroscopy sequence. Metabolite concentrations were estimated using LCModel, combined with a simulated basis set of metabolites using published spectral parameters and either the spectrum of macromolecules measured in vivo, using an inversion recovery technique, or baseline simulated by the built-in spline function. The fitted spline function resulted in a smooth approximation of the in vivo macromolecules, but in accordance with previous studies using Subtract-QUEST could not reproduce completely all features of the in vivo spectrum of macromolecules at 14.1 T. As a consequence, the measured macromolecular 'baseline' led to a more accurate and reliable quantification at higher field strengths.Measurement Science and Technology 01/2009; · 1.44 Impact Factor
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ABSTRACT: This article presents background information related to methodology for estimating brain metabolite concentration from magnetic resonance spectroscopy (MRS) and magnetic resonance spectroscopic imaging measurements of living human brain tissue. It reviews progress related to this methodology, with emphasis placed on progress reported during the past 10 years. It is written for a target audience composed of radiologists and magnetic resonance imaging technologists. It describes in general terms the relationship between MRS signal amplitude and concentration. It then presents an overview of the many practical problems associated with deriving concentration solely from absolute measured signal amplitudes and demonstrates how a various signal calibration approaches can be successfully used. The concept of integrated signal amplitude is presented with examples that are helpful for qualitative reading of MRS data as well as for understanding the methodology used for quantitative measurements. The problems associated with the accurate measurement of individual signal amplitudes in brain spectra having overlapping signals from other metabolites and overlapping nuisance signals from water and lipid are presented. Current approaches to obtaining accurate amplitude estimates with least-squares fitting software are summarized.Topics in magnetic resonance imaging: TMRI 04/2010; 21(2):115-28.