Are you correcting for gradient distortion? That could easily make 2%.
It looks like you used different ROIs in your comparisons.
On 11/28/2021 10:14 PM, AJ wrote:
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 *MailScanner has detected a possible fraud
attempt from "secure-web.cisco.com" claiming to be*
https://pubmed.ncbi.nlm.nih.gov/33940143/
<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>
<mailto:freesurfer-boun...@nmr.mgh.harvard.edu> on behalf of AJ
<ajcns1...@gmail.com> <mailto:ajcns1...@gmail.com>
*Sent:* Thursday, November 25, 2021 9:00 PM
*To:* Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
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*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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