Dear Osprey experts,
I have been using Osprey to analyse MEGA-PRESS data acquired in the motor cortex and (recently) occipital cortex. Until recently, I’ve been including a MM basis set (as suggested) in my job file, which has included the following parameters:
% Determine the baseline knot spacing (in ppm) for the metabolite spectra opts.fit.bLineKnotSpace = 0.55; % [ppm] Default: 0.4. % Add macromolecule and lipid basis functions to the fit? opts.fit.fitMM = 1; % OPTIONS: - 0 (no) % - 1 (yes, default) opts.fit.coMM3 = '3to2MM'; opts.fit.FWHMcoMM3 = 14;
However, for my two most recently acquired datasets, using these parameters has led to all the GABA signal being attributed to the MM3 signal (i.e., GABA:Raw Water ratio = 0 for these participants). If I comment out the
opts.fit.fitMM = 1; % OPTIONS: - 0 (no) % - 1 (yes, default) % opts.fit.coMM3 = '3to2MM'; % opts.fit.FWHMcoMM3 = 14;
I get a higher GABA:Raw Water ratio (e.g., 3.4e-5) and quantified values after segmentation are e.g., GABA:tCr = .113782. But… I get no peak at all for MM09 at 3 ppm - I didn’t know if this was an issue or not.
Based on your NMR paper, I think I have been using the MM09Hard model, which was recommended to me by @admin a while back, so I wanted to ask your opinion as to whether using the default settings for MMfit are appropriate (I could not see what this model was from the scripts in the Osprey fit directory sorry) or whether I have a bigger problem on my hands (i.e., no GABA signal despite pretty good quality data).
Thanks and I look forward to hearing your thoughts.