Hi Eric,
thank you for your help. That's right I already processed all MR.
So the contrast image is simply the difference between the two MR of the
same subject. I always thought about some SPM output in a specific model!
Thank you.
Since patients lost GM, don't you think that I should compute (BaselineGM -
FollowupGM)?
Then I will use these difference images in the compare population model.
Is this right?
Thank you so much
Cristina
----- Original Message -----
From: <[log in to unmask]>
To: "CrisTesta" <[log in to unmask]>
Cc: <[log in to unmask]>
Sent: Friday, January 13, 2006 7:32 AM
Subject: Re: [SPM] 2nd level analysis for longitudinal data
> Cristina,
>
> (Your question concerned the correct "model", I presume you did not
> mean preprocessing, segmentation, etc.) You have acquired two
> images per subject, and so the appropriate estimator of the
> population effect from each subject is simply the difference of the
> standard space GM images derived respectively from the two acquired
> images, say follow-up GM image minus baseline GM image. [As an
> aside, the issue of whether you'd modulate with the Jacobian would
> depend on whether you want the voxel-wise measures to be of local
> GM concentration (no modulation) or local GM volume (modulation) in
> standard space.] You could take this difference using imcalc or some
> other suitable MATLAB routine. These difference images would then be
> entered as the dependent variable in a population level model as you
> describe in your step 2.
>
> Eric
>
> Quoting CrisTesta <[log in to unmask]>:
>
> > Dear SPMers,
> > I have structural MR images of two AD groups (treated and
> > placebo) acquired at baseline, and follow up.
> > I processed my longitudinal data following Chetelat's protocol
> > (Neuroimage 2005) with SPM2.
> > Now I am interested in a second level analysis. I'd like to
> > compare GM tissue loss in the placebo group vs GM tissue loss in
> > the treated group, including age and gender as nuisances.
> > If I correctly understood, I have to:
> > 1) determine one con*.img for each subject;
> > 2) and then compare con*.img of subjects A with those subj B,
> > with a simple t-test ("compare population" model)
> >
> > Please, could you tell me the correct model I should use for the
> > first step (i.e. to determine one con*.img for each subject,
> > taking into account that these are longitudinal data)?
> > Thank you in advance
> >
> > Cristina
> >
> > LENITEM - Laboratory of Epidemiology Neuroimaging & Telemedicine
> > IRCCS San Giovanni di Dio FBF - The National Center for Research
> > and Care of Alzheimer's Disease
> > via Pilastroni 4, 25125 - Brescia, Italy
> > Tel: +39 030 3501 361
> > www.centroAlzheimer.it
>
>
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