Dear Michel, dear all,

I applied a brain mask (made using Ridgway's masking toolbox), and it
works pretty well. Thank you very much!

Also, now I have 2 questions concerning the toolbox:

1. When looking at a binary mask, some grey values can be seen
(intensity different from either 0 or 1, see attachment). Isn't the
intensity supposed to be just 0 or 1, since this is a binary mask?

2. Can I specify the voxel dimensions somewhere while making a mask?
By default it is 2x2x2 mm, which is more than in my original image.

Thank you for your time and support,
Tanja.


On Fri, Dec 3, 2010 at 1:14 PM, michel grothe <[log in to unmask]> wrote:
> Dear Joao,
>
> So, my question would be if following the next steps you get modulated
> normalized images, corresponding to the output m0wrp[123]*.nii tissue
> classes of VBM8 Estimate & Write:
>
> 1. VBM8 Estimate & Write --> INPUTS: T1 images (in native space)
>                                         --> Spatial normalization:
> High-dimensional DARTEL (templates are provided in MNI space, as well as
> spm8\toolbox\Seg\TPM.nii)
>                                         --> DARTEL export: affine -----
> OUTPUTS: rp*.nii tissue classes (warped to DARTEL template in MNI space)
>                                         --> Modulated normalized: non-linear
> only ----- OUTPUTS: m0wrp[0123]*.nii tissue classes (in MNI space, including
> correction for individual brain sizes)
>
> 2. Run DARTEL (create Templates) --> INPUTS: rp*.nii tissue classes
>                                                     --> OUTPUTS:
> DARTEL_Templates_0-6, flow fields u_rp1*.nii
>
> 3. DARTEL Tools Create Warped --> INPUTS: flow fields u_rp1*.nii, rp*.nii
> tissue classes
>                                                  --> Modulation: preserve
> amount (modulation)
>                                                  --> OUTPUTS: mwrp*.nii
> tissue classes (in MNI space; DARTEL_Templates_0-6 were created from rp*.nii
> in MNI space, and so they are also linearly MNI aligned).
>
> Are these mwrp*.nii tissue classes corresponding to the m0wrp*.nii from the
> first step? As both are modulated versions, all you need to do is smoothing
> and stats. You don't need to add brain volume as covariate (you can still
> include age)... am I correct?
>
> Yes. The only difference between your mwrp* (derived from affinely aligned
> DARTEL exported images in VBM8) and standard m0wrp* images of the VBM8
> toolbox should be the template. While both templates are in MNI space
> (global size and shape), the template of the mwrp*-images reflect the
> average (local) anatomy of your group and the template of the m0wrp*-images
> (the IXI-template of the VBM8 toolbox) is based on the average (local)
> anatomy of a healthy adult population (I don´t know what the age-average is;
> you can find information on the creation of the VBM8-IXI-template in the
> VBM8 manual). The latter should be very close to the MNI152 template, while
> the former, well, depends on your studied group. That is, if you deal with
> populations that differ significantly from the healthy adult population
> (e.g. geriatric populations) than the first approach (mwrp*-images) becomes
> favourable. If your population is not expected to differ largely from the
> healthy adult population than both approaches should reveal very similar
> results and the deviation steps 2. and 3. of your processing pipeline might
> not be worth the effort.
>
> In Tanja's procedure (using New segment), the DARTEL Tools: Normalise to MNI
> space also has the option to "preserve amount (modulation)". I suppose it
> was not used. If one would use it, would still there be the need to add
> brain volume as covariate?
>
> In my opinion (and, more importantly, the one of John Ashburner),
> high-dimensionally normalised images should always be modulated. Thus, I
> assume that Tanja has used modulation. While the volumes (voxel-values) of
> your VBM8-m0wrp* images are allready 'normalised' to MNI space  and
> variations in global head/brain size have therefore allready been accounted
> for (no modulation is applied at this affine transform to MNI space),
> (Tanja´s ??) mwrp* images (based on the normal SPM8 procedure, or VBM8
> modulate affine+non-linear) reflect the native tissue volumes and therefore
> the statistical model has still to account for differences in global
> head/brain size, if these want to be removed.
> In the archives, you can find numerous discussions about the pros and cons
> of using estimates of total brain volume, total GM volume or head size
> (total intracranial volume, TIV). Also, the VBM8 manual as well as Christian
> Gasers Web-Site have separate sections dealing with removing the confound of
> different brain/head-sizes.
>
> Given that including TIV or total GM volume in the statistical model ask
> quite different questions to the data (and often give different results), an
> interesting question would be which of the two approaches the m0-approach
> resembles more closely. If the initial affine normalisation is estimated
> from the GM segment, I would assume that not modulating the so affinely
> transformed images would be similar to accounting for total GM in the
> statistical model. However, although I haven´t investigated this
> systematically, in my studies the m0-approach seems to lead to results more
> comparable to the ones obtained when accounting for TIV in the statistical
> model.
> Maybe someone else may want to comment on this.
>
> Best regards,
> Michel
>
>
> ________________________________
> Date: Fri, 3 Dec 2010 10:46:43 +0000
> From: [log in to unmask]
> Subject: Re: [SPM] Fwd: [SPM] VBM8 quesiont
> To: [log in to unmask]
>
> Dear Michel,
>
> thank you for your clarification.
>
> I also noticed that Tanja referred adding the tissue volume as covariate.
> Shouldn't that be acounted for by the modulation?
>
> I mean, in VBM8 you can write a modulated normalized non-linear only version
> of each tissue class, which produces tissue class images (m0wrp[0123]*.nii)
> in alignment with the template (DARTEL template in MNI space if you choose
> high-dimensional DARTEL normalization), that allows comparing the absolute
> amount of tissue corrected for individual brain sizes. This option is
> similar to using “Affine+non‐linear” in combination with “Global
> normalization” --> “Overall grand mean scaling – No” --> “Normalization –
> Proportional”. It is also similar to using “Affine+non‐linear” and including
> the numeric brain volume (as given in the *_seg8.txt file for each subject)
> as covariate in the statistical model (I suppose this is the option Tanja
> used). Although all 3 approaches allow comparing tissue volumes while
> correcting for individual brain size, it is recommended to use the option
> “non‐linear only” as it applies the correction directly to the data, rather
> than to the statistical model.
>
> So, my question would be if following the next steps you get modulated
> normalized images, corresponding to the output m0wrp[123]*.nii tissue
> classes of VBM8 Estimate & Write:
>
> 1. VBM8 Estimate & Write --> INPUTS: T1 images (in native space)
>                                         --> Spatial normalization:
> High-dimensional DARTEL (templates are provided in MNI space, as well as
> spm8\toolbox\Seg\TPM.nii)
>                                         --> DARTEL export: affine -----
> OUTPUTS: rp*.nii tissue classes (warped to DARTEL template in MNI space)
>                                         --> Modulated normalized: non-linear
> only ----- OUTPUTS: m0wrp[0123]*.nii tissue classes (in MNI space, including
> correction for individual brain sizes)
>
> 2. Run DARTEL (create Templates) --> INPUTS: rp*.nii tissue classes
>                                                     --> OUTPUTS:
> DARTEL_Templates_0-6, flow fields u_rp1*.nii
>
> 3. DARTEL Tools Create Warped --> INPUTS: flow fields u_rp1*.nii, rp*.nii
> tissue classes
>                                                  --> Modulation: preserve
> amount (modulation)
>                                                  --> OUTPUTS: mwrp*.nii
> tissue classes (in MNI space; DARTEL_Templates_0-6 were created from rp*.nii
> in MNI space, and so they are also linearly MNI aligned).
>
> Are these mwrp*.nii tissue classes corresponding to the m0wrp*.nii from the
> first step? As both are modulated versions, all you need to do is smoothing
> and stats. You don't need to add brain volume as covariate (you can still
> include age)... am I correct?
>
> In Tanja's procedure (using New segment), the DARTEL Tools: Normalise to MNI
> space also has the option to "preserve amount (modulation)". I suppose it
> was not used. If one would use it, would still there be the need to add
> brain volume as covariate?
>
> Thanks for any help.
>
> João
>
>
>
> On Thu, Dec 2, 2010 at 6:07 PM, michel grothe <[log in to unmask]>
> wrote:
>
> Dear Joao,
>
>>So, my questions are: At the end, you just need to smooth the
>> "mwrp1*-affine.nii" images and do the stats? These "mwrp1*-affine.nii", as
>> well as the smoothed versions and the results are in MNI space?
>
> Yes, as long as the images are written out in rp*-affine space. DARTEL
> 'create Template' warps the images to their average anatomy (the
> DARTEL-templates 1-6), and the average anatomy of x images linearly
> (12-parameters, affine transform) aligned to MNI space will also be in MNI
> space.
> If you write the images as rp*-rigidly aligned to MNI space (SPM default) in
> the VBM8 toolbox, then your images are just rotated and translated (3 +3 = 6
> parameters) to match the --orientation-- of MNI space. They are not scaled
> and thus do not conform to MNI space and will not after DARTEL-registration
> using 'create Template' and 'create warped'. These images can be warped with
> 'create Template' and subsequent 'Normalise to MNI space', i.e. VBM8
> segmented images rigidly aligned to MNI space can be used the same way as
> DARTEL imported images from SPM8-New Segment (or even 'old' segment + DARTEL
> import).
>
> Best,
> Michel
>
> ________________________________
> Date: Thu, 2 Dec 2010 17:42:14 +0000
> From: [log in to unmask]
> Subject: Re: [SPM] Fwd: [SPM] VBM8 quesiont
> To: [log in to unmask]
>
> Dear Michel and Tanja,
>
> I've been following your very useful discussion.
>
> I have a couple of related questions more:
>
> If you use the VBM8 "Estimate & Write" module to do segmentation, you can
> get the DARTEL formatted "rp*-affine.nii" tissue classes. In the VBM8 manual
> (page 18) you can read that with the Estimate & Write module "The volumes
> “rp1*‐affine.nii” and “rp2*‐affine.nii” will be written. These are the grey
> (rp1) and white
> (rp2) matter segments after an affine registration to the MNI template".
> After that it is only suggested to run only the Modules "Run DARTEL (create
> Templates)" with "rp*-affine.nii" input, and finally the "Create warped"
> with flow fields "u_*.nii" and "rp*-affine.nii" inputs. This "Create warped"
> module has the option to "Preserve Amount (Modulation)".
> Also in the beggining of this page you can read "This option uses affine
> registered GM and WM segments and modulates the segmentations for nonlinear
> effects only, which accounts for brain size. No additional normalization to
> MNI space is
> necessary, because the DARTEL template is provided in that space."
>
> So, my questions are: At the end, you just need to smooth the
> "mwrp1*-affine.nii" images and do the stats? These "mwrp1*-affine.nii", as
> well as the smoothed versions and the results are in MNI space?
>
> Thanks for your help,
>
> João Duarte
>
>
>
> On Thu, Dec 2, 2010 at 3:31 PM, michel grothe <[log in to unmask]>
> wrote:
>
> Dear Tanja,
> 1. An absolute Threshold of 0.2 is totally acceptable and much more common
> than 0.01. Alternatively you can apply a brainmask for analysis (e.g. see
> Ridgway et al, 2009; http://www.ncbi.nlm.nih.gov/pubmed/18848632).
> 2. DARTEL 'Create Template' high-dimensionally registers your subjects to
> their average-anatomy, represented by Template_6. This template will most
> probably differ from MNI space (Normal brains are on average smaller than
> the MNI-template). This is why DARTEL 'Normalise to MNI space' estimates an
> (12-parameter) affine transform from Template_6 to MNI space and combines
> this transform with the individual DARTEL flow-fields. The scheme is:
> Native --DARTEL--> Template_6 --affine--> MNI Template, where the last
> transform is the same for each subject and aims to model global brain size
> (and shape) differences between the average anatomy of your specific group
> and the MNI Template.
> Your Template_6 will not be transformed to MNI space, which is why you see
> the disagreement with your results, which are derived from your warped
> tissue-classes in MNI space.
>
> The best would be to overlay your results on a template based on the images
> you used for the stats, that is an average of your warped tissue-classes (or
> warped structurals as explained in my previous mail). You can use imcalc for
> this: Expression: mean(X); Options: Yes, read images in data matrix (--> X).
> This template can be considered something like 'average anatomy of the group
> in MNI space' and best matches the space of your results.
>
> BTW, the avgT1_Dartel_IXI550_MNI152.nii is specific to the VBM8-toolbox and
> is not an official MNI template (although given that it is based on an
> average of the normal population aligned to MNI space, it should be very
> similar to MNI152, which is the most widely used official template of MNI
> space).
>
> Hope this helps,
> Michel
>
>> Date: Thu, 2 Dec 2010 14:42:28 +0100
>> From: [log in to unmask]
>> Subject: Re: [SPM] Fwd: [SPM] VBM8 quesiont
>> To: [log in to unmask]
>>
>> Dear all,
>>
>> I also wanted to note that for Factorial design specification I use
>> Threshold masking -> absolute threshold 0.01. I tried higher values,
>> it gives better results if threshold is 0.2 (but only while
>> overlapping the statistics on any MNI template, not Template_6.nii).
>>
>> Therefore, I have 2 questions.
>>
>> 1. Is threshold of 0.2 considered too high or acceptable?
>> 2. The Template_6.nii is smaler than any MNI template, so is it or is
>> it not normalized to MNI at step "Run DARTEL (Create Templates)"?
>>
>> Thank you,
>> Tanja.
>>
>>
>> On Thu, Dec 2, 2010 at 1:17 PM, Tetiana Dadakova <[log in to unmask]>
>> wrote:
>> > Dear Michel,
>> >
>> > thank you for your reply.
>> >
>> > In attachment you can see statistics overlaid on template
>> > avgT1_Dartel_IXI550_MNI152.nii. It is better, but still not good
>> > enough. (Is it the MNI template you mentioned or is there other
>> > standard MNI template in SPM?)
>> >
>> > I am a bit confused about the Template6.nii. It is written in VBM
>> > Tutorial by John Ashburner (this one
>> > http://www.fil.ion.ucl.ac.uk/~john/misc/VBMclass10.pdf) that
>> > "...Template 6.nii. This template is registered to MNI space (affine
>> > transform), allowing the transformations to be combined so that all
>> > the individual spatially normalised scans can also be brought into MNI
>> > space."
>> > Therefore, if I understand correctly, Template6.nii is in MNI space,
>> > right?
>> >
>> > Thanks again, I appreciate your help,
>> > Tanja.
>> >
>> >
>> >
>> >
>> > On Thu, Dec 2, 2010 at 12:30 PM, michel grothe <[log in to unmask]>
>> > wrote:
>> >> Dear Tanja,
>> >> I suppose that the template in the attached image is your
>> >> DARTEL-Template6.
>> >> This would explain the mismatch of the overlayed results, which are in
>> >> MNI
>> >> space (The MNI template brain is a bit bigger than average anatomy).
>> >> Try
>> >> projecting them on a standard MNI-template or create your
>> >> 'group-specific'-MNI-template by warping and averaging the structurals
>> >> using
>> >> 'Normalize to MNI space' (input: u_rc1*, T1-structurals, Template6; no
>> >> modulation, no or only small smoothing).
>> >>
>> >> Hope this helps,
>> >> Michel
>> >>
>> >>> Date: Wed, 1 Dec 2010 20:38:58 +0100
>> >>> From: [log in to unmask]
>> >>> Subject: [SPM] Fwd: [SPM] VBM8 quesiont
>> >>> To: [log in to unmask]
>> >>>
>> >>> Dear Michel,
>> >>>
>> >>> thank you for your answer. I tried to do just 3 steps, according to
>> >>> your mail. It looks a little better, but still something is wrong with
>> >>> template.
>> >>>
>> >>> In the attachment you can see the statistics overlaid on the
>> >>> Template6.nii.
>> >>>
>> >>> Do you have any idea what can be the problem, at which step can I make
>> >>> a mistake?
>> >>>
>> >>> The steps:
>> >>> 0. Reorient all the images to AC-PC line (most of images are .nii, but
>> >>> some are .img/.hdr)
>> >>> 1. Segmentation: Tools -> New Segment
>> >>> 2. DARTEL Tools -> Run DARTEL (Create Template) (input: rc1*.nii,
>> >>> rc2*.nii, rc3*.nii)
>> >>> 3. DARTEL Tools -> Normalize to MNI space (input: u_rc1*.nii,
>> >>> Template6.nii)
>> >>> 4. Factorial design specification (2 sample t-test, covariates: age,
>> >>> tissue volume)
>> >>>
>> >>> Thank you,
>> >>> Tanja.
>> >>>
>> >>>
>> >>> On Fri, Nov 26, 2010 at 9:26 PM, michel grothe
>> >>> <[log in to unmask]>
>> >>> wrote:
>> >>> > Dear Tanja,
>> >>> > there is a problem wit your processing steps. You´d normally
>> >>> > directly
>> >>> > warp
>> >>> > the images to MNI space, i.e. omit steps 3 and 4. The "Normalize to
>> >>> > MNI
>> >>> > space" option in SPM8 estimates an affine transform from the DARTEL
>> >>> > template
>> >>> > (specify your DARTEL-template_6 here) to the MNI-template and
>> >>> > combines
>> >>> > it
>> >>> > with the individual DARTEL flow-fields to warp each subject directly
>> >>> > from
>> >>> > native space to MNI-space (better "average anatomy of your sample in
>> >>> > MNI
>> >>> > space"). Step 3 and 4 had to be used in SPM5 but are not necessary
>> >>> > anymore
>> >>> > in SPM8. The "create warped"-option is only for the case you don´t
>> >>> > want
>> >>> > to
>> >>> > normalise to MNI space (but to the pure average anatomy of your
>> >>> > sample).
>> >>> >
>> >>> > Best,
>> >>> > Michel
>> >>> >
>> >>> >> Date: Fri, 26 Nov 2010 16:33:18 +0100
>> >>> >> From: [log in to unmask]
>> >>> >> Subject: [SPM] VBM8 quesiont
>> >>> >> To: [log in to unmask]
>> >>> >>
>> >>> >> Dear SPM list,
>> >>> >>
>> >>> >> I have a problem with VBM8 data processing. When I try to overlay
>> >>> >> statistics on the template (wTemplate6.nii), it seems that the
>> >>> >> template is either shifted or the size of the template doesn't
>> >>> >> correspond (the significant clusters are supposed to be in gray
>> >>> >> matter
>> >>> >> region, see attached image).
>> >>> >>
>> >>> >> 1. Could you please explain to me what can be the problem? Can it
>> >>> >> be
>> >>> >> the problem of wrong template generation or of statistical
>> >>> >> calculations?
>> >>> >> 2. At which of the following step is the smoothing done?
>> >>> >>
>> >>> >> Here are the steps I take
>> >>> >> 1. Segmentation with Tools -> New Segment
>> >>> >> 2. Creating DARTEL template Template6.nii with Tools -> DARTEL
>> >>> >> Tools
>> >>> >> -> Run DARTEL (create Templates)
>> >>> >> 3. Normalizing Template6.nii to MNI with Spatial -> Normalise:
>> >>> >> Estimate & Write (get wTemplate6.nii)
>> >>> >> 4. Warping segmented images with Tools -> DARTEL Tools -> Create
>> >>> >> Warped
>> >>> >> 5. Normalizing warped images to MNI with Tools -> DARTEL Tools ->
>> >>> >> Normalize to MNI Space (using wTemplate6.nii here)
>> >>> >>
>> >>> >> Thank you for your time,
>> >>> >> Tanja.
>> >>> >
>> >>
>> >
>
>
>