Numerical Design of Double Quantum Coherence Filter for the Detection of Myo-Inositol In vivo

Purpose : A numerical method of designing a multiple quantum filter (MQF) is presented for the optimum detection of myo-inositol (mI), an important brain metabolite, by using in vivo proton nuclear magnetic resonance spectroscopy (1HMRS). Materials and Methods : Starting from the characterization of the metabolite, the filter design includes the optimization of the sequence parameters such as the two echo times (TEs), the mixing time (TM), and the flip angle and offset frequency of the 3rd 90。pulse which converts multiple quantum coherences (MQCs) back into single quantum coherences (SQCs). The optimized filter was then tested both in phantom and in human brains. Results : The results demonstrate that the proposed MQF can improve the signal-tobackground ratio of the target metabolite by a factor of more than three by effectively suppressing the signal from the background metabolites. Conclusion : By incorporating a numerical method into the design of MQFs in 1HMRS the spectral integrity of a target metabolite, in particular, with a complicated spin system can be substantially enhanced.