Quantization of ME-COSI Data With Prior Knowledge Fitting
نویسندگان
چکیده
Introduction: Multi-Echo enhanced Correlated Spectroscopic Imaging (ME-COSI) (1) combines two-dimensional Magnetic Resonance Spectroscopy (2D MRS) with 2D spatial encoding. 2D MRS improves over 1D MRS by allowing detection of “cross peaks” due to J-coupling interactions and resolving such peaks from other co-resonant metabolites (2). While ME-COSI has been introduced and evaluated qualitatively, data generated by such fast 4D MRSI techniques have typically lower resolution than conventional sequences and have yet to be quantified. The goal of this study is to quantify metabolite ratios in ME-COSI data through ProFit (3), a prior knowledge fitting algorithm. Analogous to LC Model (4) and VarPro, ProFit fits acquired data to a prior-knowledge basis set and works in both the time and frequency domains using parameters such as field strength and bandwidth.
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