Re: [Freesurfer] Mean thickness estimation {Disarmed}
Hi Stephanie
I see. Yes, I guess this is ok, you just want to be careful when tossing
datasets that you aren’t biasing your results. Always better to look at them if
you can. Big errors are pretty obvious and can be found quite rapidly (e.g. by
zipping through a bunch of snapshots with nmovie_qt)
Cheers
Bruce
From: freesurfer-boun...@nmr.mgh.harvard.edu
On Behalf Of Stephanie K
Sent: Friday, November 20, 2020 6:25 AM
To: Freesurfer support list
Subject: Re: [Freesurfer] Mean thickness estimation {Disarmed}
External Email - Use Caution
Hi Bruce,
No, I don’t think that you’ve misunderstood. I was asking about cohorts that
had not been visually inspected in my first message and then in my last message
I wanted to check that I didn’t need to also remove people from visually
inspected data based on statistical outliers (as a further step). In
conclusion, from what I’ve understood: if there is no visual inspection of
data, it is best to remove statistical outliers (based on standard deviations)
even for global measures such estimated intracranial volume, mean thickness
from left and right hemispheres. When data is visually inspected, there is no
need to remove any data based on statistical outliers even if those exist as
these should be good quality. For the visual inspected data, I have kept all
participants (which have an acceptable cortical surface reconstruction rating)
for the regional variables and I also retained all participants for global
measures (thickness of mean hemisphere, estimated intracranial volume) as the
data had been processed and removed from further Freesurfer processing if they
had severe artifacts or irregularities.
Many thanks for your advice.
On Thursday, November 19, 2020, Fischl, Bruce
mailto:bfis...@mgh.harvard.edu>> wrote:
Hi Stephanie
Sorry, I think I misunderstood. If you have visually inspected the analysis
results and think that they are accurate then you definitely should leave those
subjects in
Cheers
Bruce
From:
freesurfer-boun...@nmr.mgh.harvard.edu<mailto:freesurfer-boun...@nmr.mgh.harvard.edu>
mailto:freesurfer-boun...@nmr.mgh.harvard.edu>>
On Behalf Of Stephanie K
Sent: Thursday, November 19, 2020 4:19 PM
To: Freesurfer support list
mailto:freesurfer@nmr.mgh.harvard.edu>>
Subject: Re: [Freesurfer] Mean thickness estimation {Disarmed}
External Email - Use Caution
Hi Bruce,
Is it also necessary to remove outliers (eg. 3 SD from the mean) for
Freesurfer structural measures of MRI images that have been visually inspected
as a further data cleaning step?
I really appreciate your help.
Thanks
On Thu, Nov 19, 2020 at 3:55 PM Fischl, Bruce
mailto:bfis...@mgh.harvard.edu>> wrote:
Hi Stephanie
I think that is always a good idea, unless for some reason it isn’t possible
Cheers
Bruce
From:
freesurfer-boun...@nmr.mgh.harvard.edu<mailto:freesurfer-boun...@nmr.mgh.harvard.edu>
mailto:freesurfer-boun...@nmr.mgh.harvard.edu>>
On Behalf Of Stephanie K
Sent: Thursday, November 19, 2020 2:14 AM
To: freesurfer@nmr.mgh.harvard.edu<mailto:freesurfer@nmr.mgh.harvard.edu>
Subject: Re: [Freesurfer] Mean thickness estimation
External Email - Use Caution
Hi Bruce,
Thanks for the prompt reply. It is my understanding that l_thickness,
r_thickness and estimated intracranial volume are accurately measured. Would I
still need to identify and remove outliers if visual inspection of the images
has not been done?
Many thanks,
Stephanie
On Wed, Nov 18, 2020 at 5:24 PM Stephanie K
mailto:rklin...@gmail.com>> wrote:
Hi,
I want to estimate the mean cortical thickness. For this I have summed the
thickness across all 34 regions mapped to the Desikan-Killiany atlas. However,
I also have the average mean thickness of left and right hemispheres (direct
output variables of Freesurfer). As there is no visual inspection of the
imaging in the particular cohort, I remove measures that are 3 standard
deviations above or below the mean. Hence, I may expect more outliers to be
removed when I take the average across the regions. I am using these brain
measures as outcomes in association analyses with the genetic score as the
exposure. For the mean thickness (averaged across the left and right hemisphere
thickness variables of freesurfer after removing outliers), the regression
coefficients have a smaller standard deviation than with thickness averaged
across the 34 regions. I’m not sure which one to use - which one is more
accurate? When I look at the mean thickness (which I derived using 34 regions)
and it’s standard deviation, it is similar to that of the average mean
thickness across the two hemispheres as well as the standard deviation of that.
Can you suggest what is most accurate please and what the difference is between
the mean thickness across the two hemispheres obtained from freesurfer and
those calculated across the regions? Why does one r
Re: [Freesurfer] Mean thickness estimation {Disarmed}
External Email - Use Caution
Hi Bruce,
No, I don’t think that you’ve misunderstood. I was asking about cohorts
that had not been visually inspected in my first message and then in my
last message I wanted to check that I didn’t need to also remove people
from visually inspected data based on statistical outliers (as a further
step). In conclusion, from what I’ve understood: if there is no visual
inspection of data, it is best to remove statistical outliers (based on
standard deviations) even for global measures such estimated intracranial
volume, mean thickness from left and right hemispheres. When data is
visually inspected, there is no need to remove any data based on
statistical outliers even if those exist as these should be good quality.
For the visual inspected data, I have kept all participants (which have an
acceptable cortical surface reconstruction rating) for the regional
variables and I also retained all participants for global measures
(thickness of mean hemisphere, estimated intracranial volume) as the data
had been processed and removed from further Freesurfer processing if they
had severe artifacts or irregularities.
Many thanks for your advice.
On Thursday, November 19, 2020, Fischl, Bruce
wrote:
> Hi Stephanie
>
>
>
> Sorry, I think I misunderstood. If you have visually inspected the
> analysis results and think that they are accurate then you definitely
> should leave those subjects in
>
>
>
> Cheers
>
> Bruce
>
>
>
> *From:* freesurfer-boun...@nmr.mgh.harvard.edu <
> freesurfer-boun...@nmr.mgh.harvard.edu> *On Behalf Of *Stephanie K
> *Sent:* Thursday, November 19, 2020 4:19 PM
> *To:* Freesurfer support list
> *Subject:* Re: [Freesurfer] Mean thickness estimation {Disarmed}
>
>
>
> *External Email - Use Caution*
>
> Hi Bruce,
>
>
>
> Is it also necessary to remove outliers (eg. 3 SD from the mean)
> for Freesurfer structural measures of MRI images that have been visually
> inspected as a further data cleaning step?
>
>
>
> I really appreciate your help.
>
>
>
> Thanks
>
>
>
> On Thu, Nov 19, 2020 at 3:55 PM Fischl, Bruce
> wrote:
>
> Hi Stephanie
>
>
>
> I think that is always a good idea, unless for some reason it isn’t
> possible
>
>
>
> Cheers
>
> Bruce
>
>
>
> *From:* freesurfer-boun...@nmr.mgh.harvard.edu <
> freesurfer-boun...@nmr.mgh.harvard.edu> *On Behalf Of *Stephanie K
> *Sent:* Thursday, November 19, 2020 2:14 AM
> *To:* freesurfer@nmr.mgh.harvard.edu
> *Subject:* Re: [Freesurfer] Mean thickness estimation
>
>
>
> *External Email - Use Caution*
>
> Hi Bruce,
>
>
>
> Thanks for the prompt reply. It is my understanding that l_thickness,
> r_thickness and estimated intracranial volume are accurately measured.
> Would I still need to identify and remove outliers if visual inspection of
> the images has not been done?
>
>
>
> Many thanks,
>
> Stephanie
>
>
>
> On Wed, Nov 18, 2020 at 5:24 PM Stephanie K wrote:
>
> Hi,
>
> I want to estimate the mean cortical thickness. For this I have summed the
> thickness across all 34 regions mapped to the Desikan-Killiany atlas.
> However, I also have the average mean thickness of left and right
> hemispheres (direct output variables of Freesurfer). As there is no visual
> inspection of the imaging in the particular cohort, I remove measures that
> are 3 standard deviations above or below the mean. Hence, I may expect more
> outliers to be removed when I take the average across the regions. I am
> using these brain measures as outcomes in association analyses with the
> genetic score as the exposure. For the mean thickness (averaged across the
> left and right hemisphere thickness variables of freesurfer after removing
> outliers), the regression coefficients have a smaller standard deviation
> than with thickness averaged across the 34 regions. I’m not sure which one
> to use - which one is more accurate? When I look at the mean thickness
> (which I derived using 34 regions) and it’s standard deviation, it is
> similar to that of the average mean thickness across the two hemispheres as
> well as the standard deviation of that. Can you suggest what is most
> accurate please and what the difference is between the mean thickness
> across the two hemispheres obtained from freesurfer and those calculated
> across the regions? Why does one result in more precision than in the other?
>
>
>
> Thank you!
>
> ___
> Freesurfer mailing list
> Freesurfer@nmr.mgh.harvard.edu
> *MailScanner has detected a possible fraud attempt from
> "secure-web.cisco.com" claiming to
Re: [Freesurfer] Mean thickness estimation {Disarmed}
Hi Stephanie
Sorry, I think I misunderstood. If you have visually inspected the analysis
results and think that they are accurate then you definitely should leave those
subjects in
Cheers
Bruce
From: freesurfer-boun...@nmr.mgh.harvard.edu
On Behalf Of Stephanie K
Sent: Thursday, November 19, 2020 4:19 PM
To: Freesurfer support list
Subject: Re: [Freesurfer] Mean thickness estimation {Disarmed}
External Email - Use Caution
Hi Bruce,
Is it also necessary to remove outliers (eg. 3 SD from the mean) for
Freesurfer structural measures of MRI images that have been visually inspected
as a further data cleaning step?
I really appreciate your help.
Thanks
On Thu, Nov 19, 2020 at 3:55 PM Fischl, Bruce
mailto:bfis...@mgh.harvard.edu>> wrote:
Hi Stephanie
I think that is always a good idea, unless for some reason it isn’t possible
Cheers
Bruce
From:
freesurfer-boun...@nmr.mgh.harvard.edu<mailto:freesurfer-boun...@nmr.mgh.harvard.edu>
mailto:freesurfer-boun...@nmr.mgh.harvard.edu>>
On Behalf Of Stephanie K
Sent: Thursday, November 19, 2020 2:14 AM
To: freesurfer@nmr.mgh.harvard.edu<mailto:freesurfer@nmr.mgh.harvard.edu>
Subject: Re: [Freesurfer] Mean thickness estimation
External Email - Use Caution
Hi Bruce,
Thanks for the prompt reply. It is my understanding that l_thickness,
r_thickness and estimated intracranial volume are accurately measured. Would I
still need to identify and remove outliers if visual inspection of the images
has not been done?
Many thanks,
Stephanie
On Wed, Nov 18, 2020 at 5:24 PM Stephanie K
mailto:rklin...@gmail.com>> wrote:
Hi,
I want to estimate the mean cortical thickness. For this I have summed the
thickness across all 34 regions mapped to the Desikan-Killiany atlas. However,
I also have the average mean thickness of left and right hemispheres (direct
output variables of Freesurfer). As there is no visual inspection of the
imaging in the particular cohort, I remove measures that are 3 standard
deviations above or below the mean. Hence, I may expect more outliers to be
removed when I take the average across the regions. I am using these brain
measures as outcomes in association analyses with the genetic score as the
exposure. For the mean thickness (averaged across the left and right hemisphere
thickness variables of freesurfer after removing outliers), the regression
coefficients have a smaller standard deviation than with thickness averaged
across the 34 regions. I’m not sure which one to use - which one is more
accurate? When I look at the mean thickness (which I derived using 34 regions)
and it’s standard deviation, it is similar to that of the average mean
thickness across the two hemispheres as well as the standard deviation of that.
Can you suggest what is most accurate please and what the difference is between
the mean thickness across the two hemispheres obtained from freesurfer and
those calculated across the regions? Why does one result in more precision than
in the other?
Thank you!
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Re: [Freesurfer] Mean thickness estimation {Disarmed}
External Email - Use Caution Hi Bruce, Is it also necessary to remove outliers (eg. 3 SD from the mean) for Freesurfer structural measures of MRI images that have been visually inspected as a further data cleaning step? I really appreciate your help. Thanks On Thu, Nov 19, 2020 at 3:55 PM Fischl, Bruce wrote: > Hi Stephanie > > > > I think that is always a good idea, unless for some reason it isn’t > possible > > > > Cheers > > Bruce > > > > *From:* freesurfer-boun...@nmr.mgh.harvard.edu < > freesurfer-boun...@nmr.mgh.harvard.edu> *On Behalf Of *Stephanie K > *Sent:* Thursday, November 19, 2020 2:14 AM > *To:* freesurfer@nmr.mgh.harvard.edu > *Subject:* Re: [Freesurfer] Mean thickness estimation > > > > *External Email - Use Caution* > > Hi Bruce, > > > > Thanks for the prompt reply. It is my understanding that l_thickness, > r_thickness and estimated intracranial volume are accurately measured. > Would I still need to identify and remove outliers if visual inspection of > the images has not been done? > > > > Many thanks, > > Stephanie > > > > On Wed, Nov 18, 2020 at 5:24 PM Stephanie K wrote: > > Hi, > > I want to estimate the mean cortical thickness. For this I have summed the > thickness across all 34 regions mapped to the Desikan-Killiany atlas. > However, I also have the average mean thickness of left and right > hemispheres (direct output variables of Freesurfer). As there is no visual > inspection of the imaging in the particular cohort, I remove measures that > are 3 standard deviations above or below the mean. Hence, I may expect more > outliers to be removed when I take the average across the regions. I am > using these brain measures as outcomes in association analyses with the > genetic score as the exposure. For the mean thickness (averaged across the > left and right hemisphere thickness variables of freesurfer after removing > outliers), the regression coefficients have a smaller standard deviation > than with thickness averaged across the 34 regions. I’m not sure which one > to use - which one is more accurate? When I look at the mean thickness > (which I derived using 34 regions) and it’s standard deviation, it is > similar to that of the average mean thickness across the two hemispheres as > well as the standard deviation of that. Can you suggest what is most > accurate please and what the difference is between the mean thickness > across the two hemispheres obtained from freesurfer and those calculated > across the regions? Why does one result in more precision than in the other? > > > > Thank you! > > ___ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://secure-web.cisco.com/1KPUR-tLJEURgzYmremNK46BwlQzhr2HuE-Vgj0d_IfX_gecAUGN6QjCWYLIn3brTZNmVndmFck4JXbECP-4ChBCCB9on11GCIcDXo_CeNsBG78TW3Un3dAkQZk9obRuWPnrYHXzp4kS7t-Y4GsaRBH04naRD0rppbxKez7XlIyHvl1NMwlQaEMRHOk6FqYoTIVHV6UrlC5oR6DZFRClnWLATwzWDCvj5zCYsdJ7pt7xmr1fz3Jml3iS6BjOivmfV4vWBZ-x-rpFZ_zoHRv07WA/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer ___ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
