Dear SPM 'ers
One of the major issues in the use of any analysis technique is its
"real-life" ability to detect change.
We wanted to get an idea of the degree of change (i.e. % change) between
two
groups that can be detected using SPM and the usual number of subjects.
To achieve this we took [18F]-setoperone scans (measuring cortical
5-HT2
receptors) of 18 normal subjects. We randomly assigned them to two
groups.
We observed that SPM did not report any group differences at baseline
We then added 5%, 15%, 35% and 50% increase
in one of the groups in a bilateral frontal region in each original
image of
the group member. We compared the two groups using single subject, no
covariates and
age as a nuisance since there is a strong decline with age for [18F]
Setoperone. Scans were
normalized with a ligand specific template and smoothed at 12 mm. Since
these were parametric
images no global scaling was used.
Much to our surprise, SPM did not detect these changes using its
conventional levels of significance. Only the 50% increase showed p<0.01
at a corrected
cluster level. Please see attachment
This raises some interesting issues regarding the power of SPM to detect
these changes. Looking at the result outputs however, it suggests that
the activation had actually started appearing in the
uncorrected images, much ahead of the false positives. Could it be that
the conventional criteria (corrected values for
K and voxel) are far too conservative for this iteration.
Thanks in advance for any comments
Doug Hussey
PET Centre
Centre for Addiction and Mental Health
Toronto Canada
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