Hi everybody, I have a question about FS longitudinal post-processing. Currently I obtained some corrected results comparing a Control vs. an Experimental group (pre-post). What i would like to know is if there's a thinning in the control group or a increase in the thickness of the experimental group. I tought in create a label and extract the individual values of both timepoints and then do a t test in order to see if the mean differs to 0. How I can do that?; There is an easier way to do it? Thanks in advance
Yes, just extract the stats on each time point as done in a cross sectional analysis (but instead on the ?.long.base directories) do a paired t (or a t on the difference) to see if there is increase or decrease.
If you look at one of the reported ROI's (e.g. caudate volume, or pre-central thickness) you can directly get the values from the stats files. If you have your own ROI's you need to use segstats to get the stats for them.
Cheers, Martin
On Wed, 2012-04-11 at 19:19 +0200, Dídac Vidal wrote:
Hi everybody, I have a question about FS longitudinal post-processing. Currently I obtained some corrected results comparing a Control vs. an Experimental group (pre-post). What i would like to know is if there's a thinning in the control group or a increase in the thickness of the experimental group. I tought in create a label and extract the individual values of both timepoints and then do a t test in order to see if the mean differs to 0. How I can do that?; There is an easier way to do it? Thanks in advance
-- Dídac Vidal Piñeiro
Dept. Psychiatry and Clinical Psychobiology Faculty of Medicine University of barcelona
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Hi Martin,
I would like to compare also a Control vs. an Experimental group (pre-post), but instead of using ROIs, I am interested in a whole-brain paired t-test analysis between the two groups. Which data should I take? Would it be possible to process ?.long.base with qcache and take the "rh.thickness.fwhm20.fsaverage.mgh" files? Or maybe could I use QDEC with ?.long.base after qcache?
Thank you, Yolanda
2012/4/12 Martin Reuter mreuter@nmr.mgh.harvard.edu
Yes, just extract the stats on each time point as done in a cross sectional analysis (but instead on the ?.long.base directories) do a paired t (or a t on the difference) to see if there is increase or decrease.
If you look at one of the reported ROI's (e.g. caudate volume, or pre-central thickness) you can directly get the values from the stats files. If you have your own ROI's you need to use segstats to get the stats for them.
Cheers, Martin
On Wed, 2012-04-11 at 19:19 +0200, Dídac Vidal wrote:
Hi everybody, I have a question about FS longitudinal post-processing. Currently I obtained some corrected results comparing a Control vs. an Experimental group (pre-post). What i would like to know is if there's a thinning in the control group or a increase in the thickness of the experimental group. I tought in create a label and extract the individual values of both timepoints and then do a t test in order to see if the mean differs to 0. How I can do that?; There is an easier way to do it? Thanks in advance
-- Dídac Vidal Piñeiro
Dept. Psychiatry and Clinical Psychobiology Faculty of Medicine University of barcelona
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine at http://www.partners.org/complianceline . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail.
Hi Yolanda,
take a look at the longitudinal tutorial: http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/LongitudinalTutorial
There is a section that hints at the post-processing as far as we have implemented it. Based on a longitudinal qdec table you can run long_mris_slopes to create rate or percent change maps for each subject and then run qdec on these for the cross sectional comparison.
Also I can make available a newer version of that script as lots of small things have changed since last year, let me know.
Best, Martin
On Tue, 2012-07-03 at 15:58 +0200, Yolanda Vives wrote:
Hi Martin,
I would like to compare also a Control vs. an Experimental group (pre-post), but instead of using ROIs, I am interested in a whole-brain paired t-test analysis between the two groups. Which data should I take? Would it be possible to process ?.long.base with qcache and take the "rh.thickness.fwhm20.fsaverage.mgh" files? Or maybe could I use QDEC with ?.long.base after qcache?
Thank you, Yolanda
2012/4/12 Martin Reuter mreuter@nmr.mgh.harvard.edu Yes, just extract the stats on each time point as done in a cross sectional analysis (but instead on the ?.long.base directories) do a paired t (or a t on the difference) to see if there is increase or decrease.
If you look at one of the reported ROI's (e.g. caudate volume, or pre-central thickness) you can directly get the values from the stats files. If you have your own ROI's you need to use segstats to get the stats for them. Cheers, Martin On Wed, 2012-04-11 at 19:19 +0200, Dídac Vidal wrote: > Hi everybody, > I have a question about FS longitudinal post-processing. Currently I > obtained some corrected results comparing a Control vs. an > Experimental group (pre-post). > What i would like to know is if there's a thinning in the control > group or a increase in the thickness of the experimental group. > I tought in create a label and extract the individual values of both > timepoints and then do a t test in order to see if the mean differs to > 0. > How I can do that?; There is an easier way to do it? > Thanks in advance > > -- > Dídac Vidal Piñeiro > > Dept. Psychiatry and Clinical Psychobiology > Faculty of Medicine > University of barcelona > > > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine at http://www.partners.org/complianceline . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail.
Hi Martin,
lot's of small changes can make a big change but from your phrasing i assume this isn't the case. what has changed? i would like to have the new (long_mris_slope) script.
thanks, -joost
On Tue, Jul 3, 2012 at 6:30 PM, Martin Reuter mreuter@nmr.mgh.harvard.eduwrote:
Hi Yolanda,
take a look at the longitudinal tutorial: http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/LongitudinalTutorial
There is a section that hints at the post-processing as far as we have implemented it. Based on a longitudinal qdec table you can run long_mris_slopes to create rate or percent change maps for each subject and then run qdec on these for the cross sectional comparison.
Also I can make available a newer version of that script as lots of small things have changed since last year, let me know.
Best, Martin
On Tue, 2012-07-03 at 15:58 +0200, Yolanda Vives wrote:
Hi Martin,
I would like to compare also a Control vs. an Experimental group (pre-post), but instead of using ROIs, I am interested in a whole-brain paired t-test analysis between the two groups. Which data should I take? Would it be possible to process ?.long.base with qcache and take the "rh.thickness.fwhm20.fsaverage.mgh" files? Or maybe could I use QDEC with ?.long.base after qcache?
Thank you, Yolanda
2012/4/12 Martin Reuter mreuter@nmr.mgh.harvard.edu Yes, just extract the stats on each time point as done in a cross sectional analysis (but instead on the ?.long.base directories) do a paired t (or a t on the difference) to see if there is increase or decrease.
If you look at one of the reported ROI's (e.g. caudate volume, or pre-central thickness) you can directly get the values from the stats files. If you have your own ROI's you need to use segstats to get the stats for them. Cheers, Martin On Wed, 2012-04-11 at 19:19 +0200, Dídac Vidal wrote: > Hi everybody, > I have a question about FS longitudinal post-processing. Currently I > obtained some corrected results comparing a Control vs. an > Experimental group (pre-post). > What i would like to know is if there's a thinning in the control > group or a increase in the thickness of the experimental group. > I tought in create a label and extract the individual values of both > timepoints and then do a t test in order to see if the mean differs to > 0. > How I can do that?; There is an easier way to do it? > Thanks in advance > > -- > Dídac Vidal Piñeiro > > Dept. Psychiatry and Clinical Psychobiology > Faculty of Medicine > University of barcelona > > > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine at http://www.partners.org/complianceline . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail.
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Hi Martin,
Thank you for your answer. I am also interested in testing your new scripts, if it is possible.
Regards, Yolanda
2012/7/3 Martin Reuter mreuter@nmr.mgh.harvard.edu
Hi Yolanda,
take a look at the longitudinal tutorial: http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/LongitudinalTutorial
There is a section that hints at the post-processing as far as we have implemented it. Based on a longitudinal qdec table you can run long_mris_slopes to create rate or percent change maps for each subject and then run qdec on these for the cross sectional comparison.
Also I can make available a newer version of that script as lots of small things have changed since last year, let me know.
Best, Martin
On Tue, 2012-07-03 at 15:58 +0200, Yolanda Vives wrote:
Hi Martin,
I would like to compare also a Control vs. an Experimental group (pre-post), but instead of using ROIs, I am interested in a whole-brain paired t-test analysis between the two groups. Which data should I take? Would it be possible to process ?.long.base with qcache and take the "rh.thickness.fwhm20.fsaverage.mgh" files? Or maybe could I use QDEC with ?.long.base after qcache?
Thank you, Yolanda
2012/4/12 Martin Reuter mreuter@nmr.mgh.harvard.edu Yes, just extract the stats on each time point as done in a cross sectional analysis (but instead on the ?.long.base directories) do a paired t (or a t on the difference) to see if there is increase or decrease.
If you look at one of the reported ROI's (e.g. caudate volume, or pre-central thickness) you can directly get the values from the stats files. If you have your own ROI's you need to use segstats to get the stats for them. Cheers, Martin On Wed, 2012-04-11 at 19:19 +0200, Dídac Vidal wrote: > Hi everybody, > I have a question about FS longitudinal post-processing. Currently I > obtained some corrected results comparing a Control vs. an > Experimental group (pre-post). > What i would like to know is if there's a thinning in the control > group or a increase in the thickness of the experimental group. > I tought in create a label and extract the individual values of both > timepoints and then do a t test in order to see if the mean differs to > 0. > How I can do that?; There is an easier way to do it? > Thanks in advance > > -- > Dídac Vidal Piñeiro > > Dept. Psychiatry and Clinical Psychobiology > Faculty of Medicine > University of barcelona > > > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine at http://www.partners.org/complianceline . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail.
Hi Martin,
When I convert my long qdec table to a cross sectional table to analyze for exemple percent change maps, I have some difficulties to identify my independent factor in this case, because I don't have two groups like in the longitudinal study (On-Off). Could you please help me to build this cross table from my long table?
Exemple of my longitudinal table:
fsid fsid-base group preJMS_007 JMS_007 ON postJMS_007 JMS_007 OFF preRME_063 RME_063 ON postRME_063 RME_063 OFF ... Thank you very much, yolanda
2012/7/4 Yolanda Vives yvives@pic.es
Hi Martin,
Thank you for your answer. I am also interested in testing your new scripts, if it is possible.
Regards, Yolanda
2012/7/3 Martin Reuter mreuter@nmr.mgh.harvard.edu
Hi Yolanda,
take a look at the longitudinal tutorial: http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/LongitudinalTutorial
There is a section that hints at the post-processing as far as we have implemented it. Based on a longitudinal qdec table you can run long_mris_slopes to create rate or percent change maps for each subject and then run qdec on these for the cross sectional comparison.
Also I can make available a newer version of that script as lots of small things have changed since last year, let me know.
Best, Martin
On Tue, 2012-07-03 at 15:58 +0200, Yolanda Vives wrote:
Hi Martin,
I would like to compare also a Control vs. an Experimental group (pre-post), but instead of using ROIs, I am interested in a whole-brain paired t-test analysis between the two groups. Which data should I take? Would it be possible to process ?.long.base with qcache and take the "rh.thickness.fwhm20.fsaverage.mgh" files? Or maybe could I use QDEC with ?.long.base after qcache?
Thank you, Yolanda
2012/4/12 Martin Reuter mreuter@nmr.mgh.harvard.edu Yes, just extract the stats on each time point as done in a cross sectional analysis (but instead on the ?.long.base directories) do a paired t (or a t on the difference) to see if there is increase or decrease.
If you look at one of the reported ROI's (e.g. caudate volume, or pre-central thickness) you can directly get the values from the stats files. If you have your own ROI's you need to use segstats to get the stats for them. Cheers, Martin On Wed, 2012-04-11 at 19:19 +0200, Dídac Vidal wrote: > Hi everybody, > I have a question about FS longitudinal post-processing. Currently I > obtained some corrected results comparing a Control vs. an > Experimental group (pre-post). > What i would like to know is if there's a thinning in the control > group or a increase in the thickness of the experimental group. > I tought in create a label and extract the individual values of both > timepoints and then do a t test in order to see if the mean differs to > 0. > How I can do that?; There is an easier way to do it? > Thanks in advance > > -- > Dídac Vidal Piñeiro > > Dept. Psychiatry and Clinical Psychobiology > Faculty of Medicine > University of barcelona > > > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine at http://www.partners.org/complianceline . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail.
Hi Yolanda,
you computed the percent change, now I think you want to see if it is different from zero. You don't need groups. qdec should be able to test difference from zero. If you use mri_glmfit there is a flag -osgm (one sample group mean).
Cheers, Martin ----- Original Message ----- From: Yolanda Vives To: Martin Reuter Cc: freesurfer Sent: Wednesday, July 04, 2012 7:27 AM Subject: Re: [Freesurfer] Extraction Longitudinal Stats
Hi Martin,
When I convert my long qdec table to a cross sectional table to analyze for exemple percent change maps, I have some difficulties to identify my independent factor in this case, because I don't have two groups like in the longitudinal study (On-Off). Could you please help me to build this cross table from my long table?
Exemple of my longitudinal table:
fsid fsid-base group preJMS_007 JMS_007 ON postJMS_007 JMS_007 OFF preRME_063 RME_063 ON postRME_063 RME_063 OFF ...
Thank you very much, yolanda
2012/7/4 Yolanda Vives yvives@pic.es
Hi Martin,
Thank you for your answer. I am also interested in testing your new scripts, if it is possible.
Regards, Yolanda
2012/7/3 Martin Reuter mreuter@nmr.mgh.harvard.edu
Hi Yolanda,
take a look at the longitudinal tutorial: http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/LongitudinalTutorial
There is a section that hints at the post-processing as far as we have implemented it. Based on a longitudinal qdec table you can run long_mris_slopes to create rate or percent change maps for each subject and then run qdec on these for the cross sectional comparison.
Also I can make available a newer version of that script as lots of small things have changed since last year, let me know.
Best, Martin
On Tue, 2012-07-03 at 15:58 +0200, Yolanda Vives wrote: > Hi Martin, > > I would like to compare also a Control vs. an Experimental group > (pre-post), but instead of using ROIs, I am interested in a > whole-brain paired t-test analysis between the two groups. Which data > should I take? Would it be possible to process ?.long.base with qcache > and take the "rh.thickness.fwhm20.fsaverage.mgh" files? Or maybe could > I use QDEC with ?.long.base after qcache? > > Thank you, > Yolanda > > 2012/4/12 Martin Reuter mreuter@nmr.mgh.harvard.edu > Yes, just extract the stats on each time point as done in a > cross > sectional analysis (but instead on the ?.long.base > directories) do a > paired t (or a t on the difference) to see if there is > increase or > decrease. > > If you look at one of the reported ROI's (e.g. caudate volume, > or > pre-central thickness) you can directly get the values from > the stats > files. If you have your own ROI's you need to use segstats to > get the > stats for them. > > Cheers, Martin > > On Wed, 2012-04-11 at 19:19 +0200, Dídac Vidal wrote: > > Hi everybody, > > I have a question about FS longitudinal post-processing. > Currently I > > obtained some corrected results comparing a Control vs. an > > Experimental group (pre-post). > > What i would like to know is if there's a thinning in the > control > > group or a increase in the thickness of the experimental > group. > > I tought in create a label and extract the individual values > of both > > timepoints and then do a t test in order to see if the mean > differs to > > 0. > > How I can do that?; There is an easier way to do it? > > Thanks in advance > > > > -- > > Dídac Vidal Piñeiro > > > > Dept. Psychiatry and Clinical Psychobiology > > Faculty of Medicine > > University of barcelona > > > > > > > _______________________________________________ > > Freesurfer mailing list > > Freesurfer@nmr.mgh.harvard.edu > > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > > The information in this e-mail is intended only for the person > to whom it is > addressed. If you believe this e-mail was sent to you in error > and the e-mail > contains patient information, please contact the Partners > Compliance HelpLine at > http://www.partners.org/complianceline . If the e-mail was > sent to you in error > but does not contain patient information, please contact the > sender and properly > dispose of the e-mail. > > > >
Hi Yolanda,
the new files contain some minor bug fixes and mainly some extensions, e.g. additional parameters to compute percent changes with respect to the first time point as estimated from the linear fit. Although I think the old version will work fine, it may be easier to use the newer version to prevent you from running into a problem that I already fixed.
So simply grab the files from here: http://www.nmr.mgh.harvard.edu/~mreuter/long/
backup your old ones and replace them with these.
Now, you need to pass the subjects directory explicitly (--sd flag), the flags for naming the within subject outputs has change, (--name-pc1 instead of out-pc1, because it can also be an input, when one wants to stack only the results without recomputing them). There is an option in connection with --qcache to stack the final results into a single file on the target geometry (e.g. fsaverage). This is helpful for people who want to run glmfit directly on the results.
Best, Martin
----- Original Message ----- From: Yolanda Vives To: Martin Reuter Cc: freesurfer Sent: Wednesday, July 04, 2012 4:20 AM Subject: Re: [Freesurfer] Extraction Longitudinal Stats
Hi Martin,
Thank you for your answer. I am also interested in testing your new scripts, if it is possible.
Regards, Yolanda
2012/7/3 Martin Reuter mreuter@nmr.mgh.harvard.edu
Hi Yolanda,
take a look at the longitudinal tutorial: http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/LongitudinalTutorial
There is a section that hints at the post-processing as far as we have implemented it. Based on a longitudinal qdec table you can run long_mris_slopes to create rate or percent change maps for each subject and then run qdec on these for the cross sectional comparison.
Also I can make available a newer version of that script as lots of small things have changed since last year, let me know.
Best, Martin
On Tue, 2012-07-03 at 15:58 +0200, Yolanda Vives wrote: > Hi Martin, > > I would like to compare also a Control vs. an Experimental group > (pre-post), but instead of using ROIs, I am interested in a > whole-brain paired t-test analysis between the two groups. Which data > should I take? Would it be possible to process ?.long.base with qcache > and take the "rh.thickness.fwhm20.fsaverage.mgh" files? Or maybe could > I use QDEC with ?.long.base after qcache? > > Thank you, > Yolanda > > 2012/4/12 Martin Reuter mreuter@nmr.mgh.harvard.edu > Yes, just extract the stats on each time point as done in a > cross > sectional analysis (but instead on the ?.long.base > directories) do a > paired t (or a t on the difference) to see if there is > increase or > decrease. > > If you look at one of the reported ROI's (e.g. caudate volume, > or > pre-central thickness) you can directly get the values from > the stats > files. If you have your own ROI's you need to use segstats to > get the > stats for them. > > Cheers, Martin > > On Wed, 2012-04-11 at 19:19 +0200, Dídac Vidal wrote: > > Hi everybody, > > I have a question about FS longitudinal post-processing. > Currently I > > obtained some corrected results comparing a Control vs. an > > Experimental group (pre-post). > > What i would like to know is if there's a thinning in the > control > > group or a increase in the thickness of the experimental > group. > > I tought in create a label and extract the individual values > of both > > timepoints and then do a t test in order to see if the mean > differs to > > 0. > > How I can do that?; There is an easier way to do it? > > Thanks in advance > > > > -- > > Dídac Vidal Piñeiro > > > > Dept. Psychiatry and Clinical Psychobiology > > Faculty of Medicine > > University of barcelona > > > > > > > _______________________________________________ > > Freesurfer mailing list > > Freesurfer@nmr.mgh.harvard.edu > > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > > The information in this e-mail is intended only for the person > to whom it is > addressed. If you believe this e-mail was sent to you in error > and the e-mail > contains patient information, please contact the Partners > Compliance HelpLine at > http://www.partners.org/complianceline . If the e-mail was > sent to you in error > but does not contain patient information, please contact the > sender and properly > dispose of the e-mail. > > > >
freesurfer@nmr.mgh.harvard.edu