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No, it does not affect it. The ICV is actually and *estaimated* ICV 
derived from the registration of the T1 to MNI305 space, so the T2 does 
not come into play.

On 4/17/2023 2:11 PM, Steven Meisler wrote:
>          External Email - Use Caution
>
> Hi FS team,
>
> I am running a morphometry study on a public dataset with most, but not all, 
> subjects having a T1 and T2 (about 75% have both, remaining only have T1). To 
> get the best surfaces possible, I have been including the T2 in recon-all 
> process when able to. However, this means subjects with only a T1 have 
> underwent a different processing workflow. ICV is an important predictor in 
> my study, and I was wondering if the presence of the T2 image in recon-all 
> should impact the ICV estimates? As I see it, I have the following options:
>
> 1) T2 is a factor, so I use only include T1 in recon-all so all subjects have 
> the same pipeline
> 2) T2 is a factor, so I harmonize the data as I would with data from 
> different sites/scanners
> 3) T2 is a factor, so I only analyze subjects with T1 + T2
> 4) T2 is not a factor, just use all subjects with no special considerations
>
> I am also running vertex-wise surface based morphometry, where I imagine pial 
> refinements could be more impactful. I suppose in that case, I should 
> harmonize the morphometry data, but was curious if you think something like 
> that is necessary.
>
> Thank you,
> Steven Meisler
>
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