Hi all,
when fitting MM spectra in LCModel we are facing weird NAA, Cr, Cho shape (see figure 1).
Also, the small MMs are fitted weirdly (fig. 2) having shoulders, while normally it should be a nice Gaussian/Lorentian/Voigt peak. Large MM signals look fine (fig. 3).
Is this something due to the faulty LCModel graphical representation? Or it’s something fundamentally wrong and the results can’t be trusted?
Thanks!
Best regards,
Andrei
Hate to tell you… but this is basically a near-total shim failure!
As to the MM lineshapes, is it possible that you defined your own Gaussian-shaped MM basis functions in your basis set? If yes, LCModel will think they’re normal metabolites and convolve them with its lineshape convolution kernel (giving it the same little kink that you see in the NAA model).
If you define the MMs in the LCModel control file (as is the default), this shouldn’t happen, because these components do not receive the lineshape convolution.
But again, these data are way too broad anyway.
Unfortunately I don’t have unsuppressed water for this dataset, but the residual water LW is acceptable, and I remember the scanner saying that FWHM was far from awful 
And yes, we have the MMs included in the basis set. Wanted to try this approach instead of working in control parameters. Looks like LCModel will not help in this case 
Thanks!
Oh, hold on - I’m only now getting that these are MM spectra. (Sorry, I was on my way out yesterday when I wrote my post haha!).
I would try parametrizing the MMs within the control file then (it’s not that difficult - you’ll probably have specified them with frequency and Gaussian width in your simulations as well). I assume you only have the big metabolites in your basis set (NAA, Cr, Cho)?
No problem, it happens 
Yea, we have only the large metabolites in the basis set. Just wanted to test the approach when MMs are modelled in basis (I believe, they managed to do this in Inspector). But LCModel is something different.
Thank you!
