External Email - Use Caution        

Many thanks for this.  My experience so far with SAMSEG, SynthSeg---small
sample so far.  All images were obtained 3DT1 isomeric voxel.  Just wanted
to see how the two pipelines would compare.

2 subjects who went on 6 different clinical scanners, GE or Philips:listed
below.
The coefficient of variation in the structures I'm interested in was:
normalized by the ICV (sbTIV, segmentation based TIV).
*SAMSEG*
interscan sbTIV NBrain-Stem    Ncortical-vol   NPutamen     NCaudate
NThalamus
COV 1.620754 1.937988 0.996077 1.971807 1.863897 1.549882

*SynthSEG (normalized to ICV (sbTIV)--which was obtained from running
SAMSEG on synthetic MRI (SynthSR):*
Brainstem    Cortical vol      Putamen    Caudate        Thalamus
1.48696 1.61017 2.20072 2.51099 2.16196

  Since head size does not change in the short period of time, my test
subjects (n=50) repeated scan x 2 had a sbTIV coefficient of variation of
0.93 based on SAMSEG.
 Across the 6 clinical scanners that I used (listed below), I think there
was enough tissue contrast similarities across the scanners to give a COV
around 2%, which I think is NOT bad.    Even in clinical trials with MRIs
performed on the same vendor scanner across different sites, I think the
goal is to produce variability < 2%.

  From what I can see from my data, I think you could compare across
vendors with a reasonable overall COV of around 2%, that is if the
biological effect is > 2% per time of interest.

my best,
AJ

Scanners used for controls and test subjects:
Achieva_TFE_R1
Achieva_TFE_R2
Ingenia_R1
Ingenia_R2
GE_SPGR_1529_R1
GE_SPGR_1529_R2
GE_SPGR_R1
GE_SPGR_R2
Phillip_Achieva_R1
Achieva_R2
GE_R1
GE_R2

On Sun, Nov 28, 2021, 20:41 Douglas N. Greve <dgr...@mgh.harvard.edu> wrote:

> Also samseg, see 
> https://secure-web.cisco.com/1vp8CpJRiQKmY2Jw2cEv7mIT6pEjTqFspCV00PtwvCROFBQ4enl56APRMm5vjCelLMOKTLsWx15btdt_HhgYgXyFx2liCxCnsyVuAie9mcFQKtBWyJCW52VClhUXJEaUpXlqzWLs5daHkP5TL9dUJ-iBFLSAzyXGsJH2wtHdkKGTDzh-wbeUSOVjMBNN73JLXj1DWaZd5PYDBBRcyuOXcE7q8qgXcZRkUXTWsCZ-QxenmUNJo0I-ZX_TRRmRXTl2iSj4S3VgFkY6HpZvnCw2QDxv6kepjoXi0vDAV9exqeEr_0pudttpPAtIHJVBeurZP/https%3A%2F%2Fpubmed.ncbi.nlm.nih.gov%2F33940143%2F
>
> On 11/26/2021 11:16 AM, Fischl, Bruce wrote:
>
> Hi AJ
>
> you might try SynthSeg, as that is one of the advantages of it - it isn't
> biased towards any particular MRI sequence
>
> cheers
> Bruce
> ------------------------------
> *From:* freesurfer-boun...@nmr.mgh.harvard.edu
> <freesurfer-boun...@nmr.mgh.harvard.edu>
> <freesurfer-boun...@nmr.mgh.harvard.edu> on behalf of AJ
> <ajcns1...@gmail.com> <ajcns1...@gmail.com>
> *Sent:* Thursday, November 25, 2021 9:00 PM
> *To:* Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
> <freesurfer@nmr.mgh.harvard.edu>
> *Subject:* [Freesurfer] SynthSR
>
>
>         External Email - Use Caution
> Hi,
> Could synthetic MRIs generated by the SynthSR script be potentially used
> to harmonize T1w weighted images acquired on different scanners?  Then used
> harmonized images for volumetric analyses?
> Many thanks
> AJ
>
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