Hi everyone,
I am a student who have a project for quantification of macromolecule signal using jMRUI.
I have a MM Spectra acquired with sLASER sequence from 3T scanner with TR/TE : 3000/23ms, TI750ms.
Based on that, what is the best quantitation algorithm for removing the residual metabolites, is it HLSVD or AMARES? Do somebody has an example or suggestion regarding the prior knowledge?
I tried to built the PK, guided by paper from Simicic, et.al. (2021) but not sure if I did it in correct way.
Hello, I have used AMARES for removing the residual metabolites. For this it’s important to identify the residuals correctly. If you go to the paper Simicic, et.al. (2021) in the supporting information there is a zip. file you can download an example MM spectrum and AMARES prior knowledge (for metabolite removal) to test directly and see how it works (go to folder (Metabolite_removal_PK_SV). I hope this helps you, if you have any specific questions about your PK I will be happy to answer them.
Thank you for the answer! I am really new on this field so I am so sorry for the basic questions.
I look at the database provided and the PK in the supporting information, how did you identify the residual and set the constraints? Did you identify it by looking at the peak and see the amplitude also the frequency for each metabolite?
My data is not acquired from a UHF scanner so I guess the residual is not as sharp and has fewer as in the paper.
Then is it correct if I said after the AMARES quantification, the residue is the result and can be called as the metabolite-free MM spectra?
