Quantification method for MRSI based on Hankel matrix

Abstract

Objective To study the quantification method based on Hankel matrix, the water suppression method and the metabolite imaging method for magnetic resonance spectroscopic imaging (MRSI) data. Methods Impact of Hankel data matrix on quantification MRSI methods were analyzed to obtain the most efficient Hankel matrix structure. The maximum amplitude method of the water signal peak was proposed for MRSI data water suppression. The interested metabolites information was extracted from MRSI data, and then metabolite image was obtained through bilinear interpolation algorithm. Results The minimum amplitude error and the minimum frequency error were acquired when columns number was 3/4 sampling points. The amplitude, frequency and the damping factor of the simulation data accuracy was 96.94%, 99.72% and 95.55% respectively. Hankel lanczos with partial reorthogonalization singular value decomposition (HLSVDPRO) method with 3/4 sampling points was used to form Hankel matrices. The speed of quantification decreased with the increase of sampling points. The error of quantification parameter reached minimum when the number of sampling points was 512. The water suppression degree of simulation data was 99.55% with the maximum amplitude water suppression method. Conclusions The accuracy and the speed of the quantification are promoted with an optimized Hankel matrix structure for the MRSI quantization method. The optimal length of sampling points is 512. The maximum amplitude method can suppress water perfectly. Doctors can detect the presence of tumor regions in human body at the (super) early stage by metabolite information images. Key words: Magnetic resonance spectrum imaging; Hankel matrix; Singular value decomposition; Water suppressed; Metabolite image