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Hi experts,
I have following question from one of the reviewers regarding recon-all pipeline: *"Was geometric distortion corrected? If not, this should be discussed or mentioned in the study limitation."* I was wondering if the reviewer is referring to following step in the recon-all pipeline. Could you please help me in addressing this concern by the reviewer?
Thanks. MJ Cortical Parcellation (-<no>cortparc, -<no>cortparc2) Assigns a neuroanatomical label to each location on the cortical surface. Incorporates both geometric information derived from the cortical model (sulcus and curvature), and neuroanatomical convention. Calls mris_ca_label. -cortparc creates label/?h.aparc.annot, and -cortparc2 creates /label/?h.aparc.a2005s.annot.
External Email - Use Caution
There are different kinds of geometric distortion that affect your data to differing extents. What kind of MRI data was in your study?
Matt.
From: freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Martin Juneja mj70481@gmail.com Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edu Date: Monday, May 13, 2019 at 6:53 PM To: Freesurfer support list freesurfer@nmr.mgh.harvard.edu Subject: [Freesurfer] Geometric distortion
External Email - Use Caution Hi experts,
I have following question from one of the reviewers regarding recon-all pipeline: "Was geometric distortion corrected? If not, this should be discussed or mentioned in the study limitation." I was wondering if the reviewer is referring to following step in the recon-all pipeline. Could you please help me in addressing this concern by the reviewer?
Thanks. MJ Cortical Parcellation (-<no>cortparc, -<no>cortparc2) Assigns a neuroanatomical label to each location on the cortical surface. Incorporates both geometric information derived from the cortical model (sulcus and curvature), and neuroanatomical convention. Calls mris_ca_label. -cortparc creates label/?h.aparc.annot, and -cortparc2 creates /label/?h.aparc.a2005s.annot.
________________________________ The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail.
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Thank you Matthew for your reply.
I just ran recon-all to get cortical thickness, area and volume values for specific ROIs using the steps here: https://surfer.nmr.mgh.harvard.edu/fswiki/VolumeRoiCorticalThickness and correlated the morphometric values with behavioral data. I am not sure how can I address reviewer's comment.
Any help would be really appreciated.
On Mon, May 13, 2019 at 5:41 PM Glasser, Matthew glasserm@wustl.edu wrote:
External Email - Use CautionThere are different kinds of geometric distortion that affect your data to differing extents. What kind of MRI data was in your study?
Matt.
*From: *freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Martin Juneja mj70481@gmail.com *Reply-To: *Freesurfer support list freesurfer@nmr.mgh.harvard.edu *Date: *Monday, May 13, 2019 at 6:53 PM *To: *Freesurfer support list freesurfer@nmr.mgh.harvard.edu *Subject: *[Freesurfer] Geometric distortion
External Email - Use Caution *Hi experts,
I have following question from one of the reviewers regarding recon-all pipeline:
*"Was geometric distortion corrected? If not, this should be discussed or mentioned in the study limitation."*
I was wondering if the reviewer is referring to following step in the recon-all pipeline. Could you please help me in addressing this concern by the reviewer?
Thanks.
MJ Cortical Parcellation (-<no>cortparc, -<no>cortparc2) Assigns a neuroanatomical label to each location on the cortical surface. Incorporates both geometric information derived from the cortical model (sulcus and curvature), and neuroanatomical convention. Calls mris_ca_label. -cortparc creates label/?h.aparc.annot, and -cortparc2 creates /label/?h.aparc.a2005s.annot.
The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail. _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Hi Martin,
probably the reviewer does not mean anything related to FS. Rather, there is distortion during image acquisition (e.g. gradient non- linearities). The reviewer probably wants to know if gradient unwarparing was done prior to running FS. That is why Matthew asked what MRI data was collected exactly (sequence, scanner etc).
Best, Martin
On Mon, 2019-05-13 at 21:06 -0700, Martin Juneja wrote:
External Email - Use CautionThank you Matthew for your reply.
I just ran recon-all to get cortical thickness, area and volume values for specific ROIs using the steps here: https://surfer.nmr.mgh.harvard.edu/fswiki/VolumeRoiCorticalThickness and correlated the morphometric values with behavioral data. I am not sure how can I address reviewer's comment.
Any help would be really appreciated.
On Mon, May 13, 2019 at 5:41 PM Glasser, Matthew glasserm@wustl.edu wrote:
External Email - Use CautionThere are different kinds of geometric distortion that affect your data to differing extents. What kind of MRI data was in your study?
Matt.
From: freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Martin Juneja mj70481@gmail.com Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edu Date: Monday, May 13, 2019 at 6:53 PM To: Freesurfer support list freesurfer@nmr.mgh.harvard.edu Subject: [Freesurfer] Geometric distortion
External Email - Use CautionHi experts,
I have following question from one of the reviewers regarding recon-all pipeline: "Was geometric distortion corrected? If not, this should be discussed or mentioned in the study limitation." I was wondering if the reviewer is referring to following step in the recon-all pipeline. Could you please help me in addressing this concern by the reviewer?
Thanks. MJ Cortical Parcellation (-<no>cortparc, -<no>cortparc2) Assigns a neuroanatomical label to each location on the cortical surface. Incorporates both geometric information derived from the cortical model (sulcus and curvature), and neuroanatomical convention. Calls mris_ca_label. -cortparc creates label/?h.aparc.annot, and -cortparc2 creates /label/?h.aparc.a2005s.annot.
The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail. _______________________________________________ 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
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For most scanners, gradient nonlinearity correction is a relatively small effect that is most prominent in the periphery of the FOV (it is a bit larger in the HCP custom scanner because of design constraints). For 3D structural images (e.g. T1w, T2w, FLAIR) there is a small amount of distortion in the readout direction as well. Both of these effects are much smaller than the distortion in the phase encoding direction of EPI images, which should always be corrected for.
Matt.
On 5/14/19, 4:59 AM, "freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Martin Reuter" <freesurfer-bounces@nmr.mgh.harvard.edu on behalf of mreuter@nmr.mgh.harvard.edu> wrote:
Hi Martin,
probably the reviewer does not mean anything related to FS. Rather, there is distortion during image acquisition (e.g. gradient non- linearities). The reviewer probably wants to know if gradient unwarparing was done prior to running FS. That is why Matthew asked what MRI data was collected exactly (sequence, scanner etc).
Best, Martin
On Mon, 2019-05-13 at 21:06 -0700, Martin Juneja wrote: > External Email - Use Caution > Thank you Matthew for your reply. > > I just ran recon-all to get cortical thickness, area and volume > values for specific ROIs using the steps here: > https://surfer.nmr.mgh.harvard.edu/fswiki/VolumeRoiCorticalThickness > and correlated the morphometric values with behavioral data. > I am not sure how can I address reviewer's comment. > > Any help would be really appreciated. > > On Mon, May 13, 2019 at 5:41 PM Glasser, Matthew glasserm@wustl.edu > wrote: > > External Email - Use Caution > > There are different kinds of geometric distortion that affect your > > data to differing extents. What kind of MRI data was in your > > study? > > > > Matt. > > > > From: freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Martin > > Juneja mj70481@gmail.com > > Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edu > > Date: Monday, May 13, 2019 at 6:53 PM > > To: Freesurfer support list freesurfer@nmr.mgh.harvard.edu > > Subject: [Freesurfer] Geometric distortion > > > > External Email - Use Caution > > Hi experts, > > > > I have following question from one of the reviewers regarding > > recon-all pipeline: > > "Was geometric distortion corrected? If not, this should be > > discussed or mentioned in the study limitation." > > I was wondering if the reviewer is referring to following step in > > the recon-all pipeline. Could you please help me in addressing this > > concern by the reviewer? > > > > Thanks. > > MJ > > Cortical Parcellation (-<no>cortparc, -<no>cortparc2) > > Assigns a neuroanatomical label to each location on the cortical > > surface. Incorporates both geometric information derived from the > > cortical model (sulcus and curvature), and neuroanatomical > > convention. Calls mris_ca_label. -cortparc creates > > label/?h.aparc.annot, and -cortparc2 creates > > /label/?h.aparc.a2005s.annot. > > > > The materials in this message are private and may contain Protected > > Healthcare Information or other information of a sensitive nature. > > If you are not the intended recipient, be advised that any > > unauthorized use, disclosure, copying or the taking of any action > > in reliance on the contents of this information is strictly > > prohibited. If you have received this email in error, please > > immediately notify the sender via telephone or return mail. > > _______________________________________________ > > 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
_______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
________________________________ The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail.
the gradient nonlinearities have almost no effect on thickness. Since they are spatially smooth they warp both the white and pial surfaces similarly, so the distance between them doesn't change much.
B0 effects can be large locally depending on your field strength and bandwidth. These are pretty localized to regions near air/tissue interfaces (mostly inferior frontal and inferior temporal). If those are not the regiosn you are finding thickness effects, then I think you are safe concluding it is not geometric distortion. In any case unless the condition you are looking at modifies the air/tissue interface it's hard to see why it would create an effect (although it can substantially distort thickness values for low-ish bandwidth sequences).
cheers Bruce
On Tue, 14 May 2019, Martin Reuter wrote:
Hi Martin,
probably the reviewer does not mean anything related to FS. Rather, there is distortion during image acquisition (e.g. gradient non- linearities). The reviewer probably wants to know if gradient unwarparing was done prior to running FS. That is why Matthew asked what MRI data was collected exactly (sequence, scanner etc).
Best, Martin
On Mon, 2019-05-13 at 21:06 -0700, Martin Juneja wrote:
External Email - Use CautionThank you Matthew for your reply.
I just ran recon-all to get cortical thickness, area and volume values for specific ROIs using the steps here: https://surfer.nmr.mgh.harvard.edu/fswiki/VolumeRoiCorticalThickness and correlated the morphometric values with behavioral data. I am not sure how can I address reviewer's comment.
Any help would be really appreciated.
On Mon, May 13, 2019 at 5:41 PM Glasser, Matthew glasserm@wustl.edu wrote:
External Email - Use CautionThere are different kinds of geometric distortion that affect your data to differing extents. What kind of MRI data was in your study?
Matt.
From: freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Martin Juneja mj70481@gmail.com Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edu Date: Monday, May 13, 2019 at 6:53 PM To: Freesurfer support list freesurfer@nmr.mgh.harvard.edu Subject: [Freesurfer] Geometric distortion
External Email - Use CautionHi experts,
I have following question from one of the reviewers regarding recon-all pipeline: "Was geometric distortion corrected? If not, this should be discussed or mentioned in the study limitation." I was wondering if the reviewer is referring to following step in the recon-all pipeline. Could you please help me in addressing this concern by the reviewer?
Thanks. MJ Cortical Parcellation (-<no>cortparc, -<no>cortparc2) Assigns a neuroanatomical label to each location on the cortical surface. Incorporates both geometric information derived from the cortical model (sulcus and curvature), and neuroanatomical convention. Calls mris_ca_label. -cortparc creates label/?h.aparc.annot, and -cortparc2 creates /label/?h.aparc.a2005s.annot.
The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail. _______________________________________________ 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
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
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Thank you so much Martin, Matthew and Bruce for all the detailed information.
Just to answer your question regarding MRI data: T1-weighted data were collected using a 3.0 Tesla Siemens Tim Trio scanner (Siemens, Erlangen, Germany). T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) images were collected over 176 sagittal slices (TR/TE/flip angle = 2.1 s/2.25 ms/12°, 256 × 256 matrix) with voxel size = 1 × 1 × 1 mm.
Also, I did not perform any gradient unwarping manually, so I am not sure if this is done automatically.
So as far as I understand from the discussion, to reply reviewer's question, can I handle that something like this:
*"Geometric distortion of T1-weighted data was not manually corrected for our current morphometric analysis. This is because T1-weighted data for this study were collected using a 3.0 Tesla Siemens Tim Trio scanner. Gradient nonlinearity correction in most of the scanners, including Siemens, has a relatively small/no effect on morphometric measures such thickness, area and volume, because morphometric measures are spatially smooth and they warp both the white and pial surfaces similarly. Therefore, the distance between these surface doesn't change much. However, such effects can be very prominent in the periphery of the FOV. For instance, B0 effects can be large and localized to regions near air/tissue interfaces (mostly inferior frontal and inferior temporal). Since our results showed the association between morphometric measures of MPFC and behavior (XYZ), therefore, our findings are not due to geometric distortion."*
I am not expert in this field, so I would really appreciate any further help.
Thanks.
On Tue, May 14, 2019 at 7:13 AM Bruce Fischl fischl@nmr.mgh.harvard.edu wrote:
the gradient nonlinearities have almost no effect on thickness. Since they are spatially smooth they warp both the white and pial surfaces similarly, so the distance between them doesn't change much.
B0 effects can be large locally depending on your field strength and bandwidth. These are pretty localized to regions near air/tissue interfaces (mostly inferior frontal and inferior temporal). If those are not the regiosn you are finding thickness effects, then I think you are safe concluding it is not geometric distortion. In any case unless the condition you are looking at modifies the air/tissue interface it's hard to see why it would create an effect (although it can substantially distort thickness values for low-ish bandwidth sequences).
cheers Bruce
On Tue, 14 May 2019, Martin Reuter wrote:
Hi Martin,
probably the reviewer does not mean anything related to FS. Rather, there is distortion during image acquisition (e.g. gradient non- linearities). The reviewer probably wants to know if gradient unwarparing was done prior to running FS. That is why Matthew asked what MRI data was collected exactly (sequence, scanner etc).
Best, Martin
On Mon, 2019-05-13 at 21:06 -0700, Martin Juneja wrote:
External Email - Use CautionThank you Matthew for your reply.
I just ran recon-all to get cortical thickness, area and volume values for specific ROIs using the steps here: https://surfer.nmr.mgh.harvard.edu/fswiki/VolumeRoiCorticalThickness and correlated the morphometric values with behavioral data. I am not sure how can I address reviewer's comment.
Any help would be really appreciated.
On Mon, May 13, 2019 at 5:41 PM Glasser, Matthew glasserm@wustl.edu wrote:
External Email - Use CautionThere are different kinds of geometric distortion that affect your data to differing extents. What kind of MRI data was in your study?
Matt.
From: freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Martin Juneja mj70481@gmail.com Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edu Date: Monday, May 13, 2019 at 6:53 PM To: Freesurfer support list freesurfer@nmr.mgh.harvard.edu Subject: [Freesurfer] Geometric distortion
External Email - Use CautionHi experts,
I have following question from one of the reviewers regarding recon-all pipeline: "Was geometric distortion corrected? If not, this should be discussed or mentioned in the study limitation." I was wondering if the reviewer is referring to following step in the recon-all pipeline. Could you please help me in addressing this concern by the reviewer?
Thanks. MJ Cortical Parcellation (-<no>cortparc, -<no>cortparc2) Assigns a neuroanatomical label to each location on the cortical surface. Incorporates both geometric information derived from the cortical model (sulcus and curvature), and neuroanatomical convention. Calls mris_ca_label. -cortparc creates label/?h.aparc.annot, and -cortparc2 creates /label/?h.aparc.a2005s.annot.
The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail. _______________________________________________ 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
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
it's not the morphometric measures that are smooth, it is the gradient nonlinearities. So they warp the gray and white surface by pretty much the same amount and preserve the thickness (unless you are using a head-only system, which you are not)
On Tue, 14 May 2019, Martin Juneja wrote:
External Email - Use Caution
Thank you so much Martin, Matthew and Bruce for all the detailed information. Just to answer your question regarding MRI data: T1-weighted data were collected using a 3.0 Tesla Siemens Tim Trio scanner (Siemens, Erlangen, Germany). T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) images were collected over 176 sagittal slices (TR/TE/flip angle = 2.1 s/2.25 ms/12°, 256 × 256 matrix) with voxel size = 1 × 1 × 1 mm.
Also, I did not perform any gradient unwarping manually, so I am not sure if this is done automatically.
So as far as I understand from the discussion, to reply reviewer's question, can I handle that something like this:
"Geometric distortion of T1-weighted data was not manually corrected for our current morphometric analysis. This is because T1-weighted data for this study were collected using a 3.0 Tesla Siemens Tim Trio scanner. Gradient nonlinearity correction in most of the scanners, including Siemens, has a relatively small/no effect on morphometric measures such thickness, area and volume, because morphometric measures are spatially smooth and they warp both the white and pial surfaces similarly. Therefore, the distance between these surface doesn't change much. However, such effects can be very prominent in the periphery of the FOV. For instance, B0 effects can be large and localized to regions near air/tissue interfaces (mostly inferior frontal and inferior temporal). Since our results showed the association between morphometric measures of MPFC and behavior (XYZ), therefore, our findings are not due to geometric distortion."
I am not expert in this field, so I would really appreciate any further help. Thanks.
On Tue, May 14, 2019 at 7:13 AM Bruce Fischl fischl@nmr.mgh.harvard.edu wrote: the gradient nonlinearities have almost no effect on thickness. Since they are spatially smooth they warp both the white and pial surfaces similarly, so the distance between them doesn't change much.
B0 effects can be large locally depending on your field strength and bandwidth. These are pretty localized to regions near air/tissue interfaces (mostly inferior frontal and inferior temporal). If those are not the regiosn you are finding thickness effects, then I think you are safe concluding it is not geometric distortion. In any case unless the condition you are looking at modifies the air/tissue interface it's hard to see why it would create an effect (although it can substantially distort thickness values for low-ish bandwidth sequences). cheers Bruce On Tue, 14 May 2019, Martin Reuter wrote: > Hi Martin, > > probably the reviewer does not mean anything related to FS. Rather, > there is distortion during image acquisition (e.g. gradient non- > linearities). The reviewer probably wants to know if gradient > unwarparing was done prior to running FS. That is why Matthew asked > what MRI data was collected exactly (sequence, scanner etc). > > Best, Martin > > On Mon, 2019-05-13 at 21:06 -0700, Martin Juneja wrote: >> External Email - Use Caution >> Thank you Matthew for your reply. >> >> I just ran recon-all to get cortical thickness, area and volume >> values for specific ROIs using the steps here: >> https://surfer.nmr.mgh.harvard.edu/fswiki/VolumeRoiCorticalThickness >> and correlated the morphometric values with behavioral data. >> I am not sure how can I address reviewer's comment. >> >> Any help would be really appreciated. >> >> On Mon, May 13, 2019 at 5:41 PM Glasser, Matthew <glasserm@wustl.edu> >> wrote: >>> External Email - Use Caution >>> There are different kinds of geometric distortion that affect your >>> data to differing extents. What kind of MRI data was in your >>> study? >>> >>> Matt. >>> >>> From: <freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Martin >>> Juneja <mj70481@gmail.com> >>> Reply-To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu> >>> Date: Monday, May 13, 2019 at 6:53 PM >>> To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu> >>> Subject: [Freesurfer] Geometric distortion >>> >>> External Email - Use Caution >>> Hi experts, >>> >>> I have following question from one of the reviewers regarding >>> recon-all pipeline: >>> "Was geometric distortion corrected? If not, this should be >>> discussed or mentioned in the study limitation." >>> I was wondering if the reviewer is referring to following step in >>> the recon-all pipeline. Could you please help me in addressing this >>> concern by the reviewer? >>> >>> Thanks. >>> MJ >>> Cortical Parcellation (-<no>cortparc, -<no>cortparc2) >>> Assigns a neuroanatomical label to each location on the cortical >>> surface. Incorporates both geometric information derived from the >>> cortical model (sulcus and curvature), and neuroanatomical >>> convention. Calls mris_ca_label. -cortparc creates >>> label/?h.aparc.annot, and -cortparc2 creates >>> /label/?h.aparc.a2005s.annot. >>> >>> The materials in this message are private and may contain Protected >>> Healthcare Information or other information of a sensitive nature. >>> If you are not the intended recipient, be advised that any >>> unauthorized use, disclosure, copying or the taking of any action >>> in reliance on the contents of this information is strictly >>> prohibited. If you have received this email in error, please >>> immediately notify the sender via telephone or return mail. >>> _______________________________________________ >>> 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 > > _______________________________________________ > 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
External Email - Use Caution
Thanks a lot Bruce.
On Tue, May 14, 2019 at 10:21 AM Bruce Fischl fischl@nmr.mgh.harvard.edu wrote:
it's not the morphometric measures that are smooth, it is the gradient nonlinearities. So they warp the gray and white surface by pretty much the same amount and preserve the thickness (unless you are using a head-only system, which you are not)
On Tue, 14 May 2019, Martin Juneja wrote:
External Email - Use CautionThank you so much Martin, Matthew and Bruce for all the detailed
information.
Just to answer your question regarding MRI data: T1-weighted data were
collected using a 3.0 Tesla
Siemens Tim Trio scanner (Siemens, Erlangen, Germany). T1-weighted
magnetization-prepared rapid
gradient-echo (MPRAGE) images were collected over 176 sagittal slices
(TR/TE/flip angle = 2.1
s/2.25 ms/12°, 256 × 256 matrix) with voxel size = 1 × 1 × 1 mm.
Also, I did not perform any gradient unwarping manually, so I am not
sure if this is done
automatically.
So as far as I understand from the discussion, to reply reviewer's
question, can I handle that
something like this:
"Geometric distortion of T1-weighted data was not manually corrected for
our current morphometric
analysis. This is because T1-weighted data for this study were collected
using a 3.0 Tesla Siemens
Tim Trio scanner. Gradient nonlinearity correction in most of the
scanners, including Siemens, has
a relatively small/no effect on morphometric measures such thickness,
area and volume, because
morphometric measures are spatially smooth and they warp both the white
and pial surfaces
similarly. Therefore, the distance between these surface doesn't change
much. However, such effects
can be very prominent in the periphery of the FOV. For instance, B0
effects can be large
and localized to regions near air/tissue interfaces (mostly inferior
frontal and inferior
temporal). Since our results showed the association between morphometric
measures of MPFC and
behavior (XYZ), therefore, our findings are not due to geometric
distortion."
I am not expert in this field, so I would really appreciate any further
help.
Thanks.
On Tue, May 14, 2019 at 7:13 AM Bruce Fischl fischl@nmr.mgh.harvard.edu
wrote:
the gradient nonlinearities have almost no effect on thickness.Since they
are spatially smooth they warp both the white and pial surfacessimilarly,
so the distance between them doesn't change much. B0 effects can be large locally depending on your field strengthand
bandwidth. These are pretty localized to regions near air/tissueinterfaces
(mostly inferior frontal and inferior temporal). If those are notthe
regiosn you are finding thickness effects, then I think you aresafe
concluding it is not geometric distortion. In any case unless the condition you are looking at modifies the air/tissue interfaceit's hard to
see why it would create an effect (although it can substantiallydistort
thickness values for low-ish bandwidth sequences). cheers Bruce On Tue, 14 May 2019, Martin Reuter wrote: > Hi Martin, > > probably the reviewer does not mean anything related to FS.Rather,
> there is distortion during image acquisition (e.g. gradient non- > linearities). The reviewer probably wants to know if gradient > unwarparing was done prior to running FS. That is why Matthewasked
> what MRI data was collected exactly (sequence, scanner etc). > > Best, Martin > > On Mon, 2019-05-13 at 21:06 -0700, Martin Juneja wrote: >> External Email - Use Caution >> Thank you Matthew for your reply. >> >> I just ran recon-all to get cortical thickness, area and volume >> values for specific ROIs using the steps here: >>https://surfer.nmr.mgh.harvard.edu/fswiki/VolumeRoiCorticalThickness
>> and correlated the morphometric values with behavioral data. >> I am not sure how can I address reviewer's comment. >> >> Any help would be really appreciated. >> >> On Mon, May 13, 2019 at 5:41 PM Glasser, Matthew <glasserm@wustl.edu>
>> wrote: >>> External Email - Use Caution >>> There are different kinds of geometric distortion that affectyour
>>> data to differing extents. What kind of MRI data was in your >>> study? >>> >>> Matt. >>> >>> From: <freesurfer-bounces@nmr.mgh.harvard.edu> on behalf ofMartin
>>> Juneja <mj70481@gmail.com> >>> Reply-To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
>>> Date: Monday, May 13, 2019 at 6:53 PM >>> To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu> >>> Subject: [Freesurfer] Geometric distortion >>> >>> External Email - Use Caution >>> Hi experts, >>> >>> I have following question from one of the reviewers regarding >>> recon-all pipeline: >>> "Was geometric distortion corrected? If not, this should be >>> discussed or mentioned in the study limitation." >>> I was wondering if the reviewer is referring to following stepin
>>> the recon-all pipeline. Could you please help me in addressingthis
>>> concern by the reviewer? >>> >>> Thanks. >>> MJ >>> Cortical Parcellation (-<no>cortparc, -<no>cortparc2) >>> Assigns a neuroanatomical label to each location on thecortical
>>> surface. Incorporates both geometric information derived fromthe
>>> cortical model (sulcus and curvature), and neuroanatomical >>> convention. Calls mris_ca_label. -cortparc creates >>> label/?h.aparc.annot, and -cortparc2 creates >>> /label/?h.aparc.a2005s.annot. >>> >>> The materials in this message are private and may containProtected
>>> Healthcare Information or other information of a sensitivenature.
>>> If you are not the intended recipient, be advised that any >>> unauthorized use, disclosure, copying or the taking of anyaction
>>> in reliance on the contents of this information is strictly >>> prohibited. If you have received this email in error, please >>> immediately notify the sender via telephone or return mail. >>> _______________________________________________ >>> 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 > > _______________________________________________ > 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
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