Hello,
I am comparing a group of healthy single-frame PET images to a group of diseased single-frame PET images. I have attempted the post processing by following the Spatial pre-processing example in the SPM12 manual, under "Auditory fMRI data", but just assuming
that instead of functional data, I have only one frame, so skipping the realignment, and using the PET image in the Normalise step, instead of all the functional fMRI images. I am programming literate so I can export the .m code into script to process all
subjects uniformly, and have done so with the process from this example. The resulting normalizations appear to be off however. They seem to be rotated in the sagittal plane by a couple of degrees in some cases, and are just generally slightly off from each
other. I think this is interfering with my analysis, as I only have 5 subjects per group (pilot study)
I also attempted the following manually, through the SPM GUI:
- Using "Display", change origins of MRI and PET manually to align with anterior commissure (best guess for PET)
- Coregister - Estimate and Reslice:
- Reference = MRI
- Source = PET
- Segment MRI
- Save forward deformation
- Normalize - Write:
- Apply deformation to MRI and coregistered PET
- Smooth PET
- 6x6x6 FWHM
- Model Selection
- Two sample T-test
Group 1 = Healthy
Group 2 = Diseased
- Explicit mask (Average MRI in MNI space)
- Results (HC < Affected)
- T Contrast = -1, 1
We see interesting results when doing a ROI analysis with a different software, but the voxel-wise analysis with SPM does not seem to agree, and we suspect it is due to less than optimal normalization to MNI space of the PET images.
Any advice is much appreciated.
Thanks,
- Eli
Houston Methodist. Leading Medicine.
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