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On Sat, Jan 13, 2024 at 11:00 AM Mirsol Choi <mir...@ualberta.ca> wrote:

> Hello,
>
> My goal is to compare the FA and MD values of hippocampal subfields (only
> inside the hippocampus) between cognitively normal, MCI, and AD subjects. I
> am unsure if this would require a voxel wise analysis or an ROI analysis…
> to my understanding this is more of a ROI analysis between subjects - is
> this assumption incorrect?
>
> Thank you,
> Peter
>
> On Sat, Jan 13, 2024 at 10:44 AM Douglas N. Greve <dgr...@mgh.harvard.edu>
> wrote:
>
>> So this is where I get confused on your intentions because you say that
>> you want to do a voxel-wise analysis of an ROI. Do you mean you want to do
>> a voxelwise analysis but only inside, eg, whole hippocampus?
>>
>> On 1/12/2024 6:07 PM, Mirsol Choi wrote:
>>
>>         External Email - Use Caution
>> Hello,
>>
>> Sorry I should have clarified. Yes, I would like to perform voxelwise
>> analysis of FA and MD values of hippocampal subfield between subjects. Is
>> this possible with free surfer?
>>
>> Thank you again for your time.
>>
>> M
>>
>> On Fri, Jan 12, 2024 at 4:05 PM Douglas N. Greve <dgr...@mgh.harvard.edu>
>> wrote:
>>
>>> oh, I thought you wanted to do an ROI analysis. You mean for a voxelwise
>>> analysis?
>>>
>>> On 1/12/2024 5:46 PM, Mirsol Choi wrote:
>>>
>>>         External Email - Use Caution
>>> Hi there,
>>>
>>>
>>> Following the first registration step, should I also run another
>>> registration command to put all fa-in-subfields.mgz for each subject onto
>>> the same space for inter subject analysis of FA values?
>>>
>>> Thanks again,
>>> M
>>>
>>> On Fri, Jan 12, 2024 at 3:00 PM Douglas N. Greve <dgr...@mgh.harvard.edu>
>>> wrote:
>>>
>>>> Map the diffusion data to the subfield space, eg,
>>>> mri_vol2vol --mov fa.nii.gz --reg register.lta --targ subfields.mgz --o
>>>> fa-in-subfields.mgz
>>>> Then run mri_segstats
>>>> mri_segstats  --ctab-default --i fa-in-subfields.mgz --seg
>>>> subfields.mgz --sum fa-in-subfields.dat
>>>>
>>>>
>>>>
>>>> On 1/12/2024 4:53 PM, Mirsol Choi wrote:
>>>>
>>>>         External Email - Use Caution
>>>> Hi there,
>>>>
>>>> Is there a way to successfully obtain FA/MD values from the hippocampus
>>>> subfields?
>>>>
>>>> Thank you,
>>>> M
>>>>
>>>>
>>>> On Fri, Jan 12, 2024 at 2:23 PM Douglas N. Greve <
>>>> dgr...@mgh.harvard.edu> wrote:
>>>>
>>>> I'm not sure what you mean. The subfields are an ROI-based analysis.
>>>>> Are you saying you want to do a voxel-based analysis (without reference to
>>>>> ROIs)?
>>>>>
>>>>> On 1/9/2024 12:05 PM, Mirsol Choi wrote:
>>>>>
>>>>>         External Email - Use Caution
>>>>>
>>>>> Hi there Freesurfer,
>>>>>
>>>>> I am currently using freesurfer to take DTI metrics (FA, MD) from
>>>>> hippocampal subfields.
>>>>> At this point of my exploration with freesurfer, I am able to
>>>>> correctly register the hippocampal subfields and diffusion data, and 
>>>>> obtain
>>>>> my FA values from the subfields. However, this is at the individual 
>>>>> subject
>>>>> level.
>>>>>
>>>>> I will eventually need to register all of my samples in the same space
>>>>> for me to do a group analysis. However I am unsure what the order of
>>>>> registration should be for this process to be feasible.
>>>>>
>>>>> Does this order seem feasible for accurate analysis?
>>>>>
>>>>> 1) recon-all all of my subjects
>>>>> 2) dt_recon all of my subjects (one of the outputs is a registration
>>>>> file, which has registered the DTI data to outputs of recon-all)
>>>>> 3) run the hippocampus segmentation command on all subjects
>>>>> (segmentHA_T1.sh) to obtain hippocampal subfield segmentation
>>>>> 4) register the segmentation file to the FA maps (output of dt_recon)
>>>>> using vol2subfield command
>>>>> 5) After creating a subfield-FA map for each subject, spatial
>>>>> normalize the samples onto the same space using *mri_vol2vol*
>>>>>
>>>>> Thank you so much for taking the time reading my question. If there is
>>>>> a different method to spatially normalizing my datasets, or if there is a
>>>>> more optimal order of registration, I'd be happy to hear from you.
>>>>>
>>>>> Thank you,
>>>>> M
>>>>>
>>>>> _______________________________________________
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