Hi Svan,

my 2p on this... 

When I had to deal with F-Dopa in controls and patients, I found that a linear registration with mutual information to the T1w, followed by the application of the warp derived from the optimised VBM was working very well... The other advantage is that you will also place DAT and VBM in the same space, so that if you want to regress out voxel-wise the VBM "confound", you'd be able to do so.

Cheers,
Gwenaelle 



> De: Sven Haller <[log in to unmask]>
> Objet: Re: [FSL] Normalize DATSCAN to MNI (ideally non-linear)
> À: [log in to unmask]
> Date: Mercredi 16 mars 2011, 10h55
> Dear Mark, Cornelius and Andreas
> 
> Thanks a lot for you input!
> 
> So far I have no experience with DatScans, and I highly
> appreciate your comments!
> 
> My idea is to do a multi-modal analysis of GM (VBM), WM
> (TBSS), and DatScan
> 
> Concerning DatScan, I fully agree with the concerns of
> Cornelius. The pattern is quite different from the
> anatomical boundaries of the basal ganglia, in particular in
> patients.
> In a previous study, we (together with Andreas) used TBSS
> preprocessing of DTI to derive a non-linear transformation
> matrix dominantly driven by the deep white matter
> structures. We then applied this matrix to SWI images
> (linear SWI to DTI, non linear to MNI using the TBSS
> transformation matrix). The results looked quite nice. So I
> was hoping to do the same thing i.e. linear DatScan to FA.
> The problem here in my view is the very peculiar image
> contrast of the DatScan images. My hope is that by this
> approach I could avoid some problems of normalization
> related to the decreased uptake predominantly in the
> posterior parts in patients.
> 
> Concerning the other question by Cornelius, I want to use a
> control ROI in occipital area (after spatial registration)
> and calculate a ratio for each voxel.
> 
> In the literature, I now found this link
> http://jnm.snmjournals.org/cgi/reprint/48/9/1459.pdf
> 
> The authors however use essential tremor (ET) patients. In
> my limited experience of DatScans, I understand that the
> variability of uptake in this pathology is considerably less
> pronounced as compared to Parkinson patients - hence less
> problems for the spatial registration. I am thus not sure
> whether this approach can be applied to my dataset ( also it
> was done in SPM2 :-( )
> 
> I would like to do randomize analyses of GM (VBM), WM
> (TBSS) and DatScan in the same subjects, therefore I would
> like to pre-process all data in FSL and co-register into MNI
> space
> 
> Thanks a lot for your help
> 
> Sven 
> 
> 
> On 16 mars 2011, at 11:18, Mark Jenkinson wrote:
> 
> > Dear Cornelius and Sven,
> > 
> > OK, I've seen Sven's images now and have a much better
> feel for it.
> > The segmentation approach for an individual structural
> sounds flawed
> > based on Cornelius's observation that the DaTScan does
> not show
> > all the structure borders clearly.  However, the
> good news is that from
> > the images it is clear that you can find the whole
> brain in the scan
> > and there main boundaries (at least brain/non-brain)
> are shown OK.
> > There is clearly a hot-spot in the middle of the scan,
> but that can be
> > dealt with by (a) hoping that the multi-modal cost
> functions (mutual
> > information, etc.) will just be OK with this, (b)
> "inverse" thresholding 
> > the image so that intensities over a certain threshold
> are capped at 
> > that value (thus eliminating the bright spots), or (c)
> using a basal
> > ganglia drived mask (from an individual segmentation
> or a standard
> > space) to do cost-function weighting and set these
> areas to zero
> > in the weight (thus ignoring their contribution to the
> overall alignment).
> > 
> > I think that there is a good chance that one of these
> options would work.
> > 
> > All the best,
> >     Mark
> > 
> > P.S. I wrote this before seeing Cornelius's linked
> images, which are
> > worse than the one Sven sent wrt brain
> boundaries.  Hopefully
> > most data looks like Sven's images, although it still
> might be possible
> > to register the images that Cornelius sent.  The
> outer border of the
> > brain is a very good boundary for registration
> within-subject.
> > 
> > 
> > On 16 Mar 2011, at 10:10, Cornelius Werner wrote:
> > 
> >> Dear Mark,
> >> 
> >> that's precisely why I think this will not work -
> the boundaries are
> >> NOT equal. In pathological DatScans the volume
> typically gets smaller
> >> (particularly the "tail" towards the occiput),
> while the anatomical
> >> structure stays the same. See this link for an
> example:
> >> 
> >> http://www.medscape.com/viewarticle/735875
> >> 
> >> or simply google DaTScan in an image search. While
> I am certainly not
> >> an PET expert, I seem to remember that DaTScans
> are somewhat difficult
> >> to analyze automatically. In our routine, we get
> semiquantitative
> >> results by our nuclear medicine staff at best.
> >> 
> >> Cheers,
> >> Cornelius
> >> 
> >> On Wed, Mar 16, 2011 at 10:50 AM, Sven Haller
> <[log in to unmask]>
> wrote:
> >>> Dear Mark
> >>> 
> >>> Thanks a lot
> >>> Try this link. I hope that it works
> >>> http://gallery.me.com/sven.haller/100063
> >>> 
> >>> Sven
> >>> 
> >>> On 16 mars 2011, at 10:20, Mark Jenkinson
> wrote:
> >>> 
> >>>> Dear Sven,
> >>>> 
> >>>> It will all be about whether you can see
> details in the images of
> >>>> anatomical boundaries like in the MRI or
> not.  Certainly the more
> >>>> "different" the images are and the less
> details you have in them
> >>>> the more it will be absolutely essential
> to register them to another
> >>>> within-subject image (using 6 dof or
> similar) as non-linear registration
> >>>> requires highly detailed images that show
> the same structures in
> >>>> each.
> >>>> 
> >>>> One approach might be (but I can't say for
> sure without seeing the
> >>>> images) to segment the basal ganglia in
> the T1-weighted image and
> >>>> use this as a registration target. 
> However, this would only be appropriate
> >>>> if the DATSCAN clearly showed only these
> boundaries and had them
> >>>> close to the anatomical boundaries.
> >>>> 
> >>>> As for showing an image - can you post it
> somewhere on the web and
> >>>> put the link to it in the email.  It
> is not possible to attach anything but the
> >>>> smallest attachments to the list (to avoid
> everyone's inbox getting swamped).
> >>>> 
> >>>> All the best,
> >>>>      Mark
> >>>> 
> >>>> 
> >>>> On 16 Mar 2011, at 09:10, Sven Haller
> wrote:
> >>>> 
> >>>>> Dear Mark
> >>>>> 
> >>>>> Thank you very much for your e-mail
> >>>>> 
> >>>>> In fact the DaTScans are very
> different to "normal" SPECT or PET, e.g. FDG PET. In the
> latter you have activity in the entire brain, so I think
> that normalization to a T1 (maybe after BET) should be
> possible (although I have no personal experience here).
> >>>>> 
> >>>>> The image of a DaTScan is
> fundamentally different (see attachment). In fact activity
> is present only in the basal ganglia. I think that therefore
> the procedure to normalize the scans should be very
> different.
> >>>>> 
> >>>>> I like FSL, and I would like to
> analyze VBM and TBSS. Therefore it would be best to analyze
> the DaTScan also in FSL, followed by a RANDOMISE analysis
> >>>>> 
> >>>>> Any help is highly appreciated
> >>>>> 
> >>>>> Sven
> >>>>> 
> >>>>> PS: The image was refused (too large).
> Maybe I can send it to you in another way??
> >>>>> 
> >>>>> 
> >>>>> On 16 mars 2011, at 09:29, Mark
> Jenkinson wrote:
> >>>>> 
> >>>>>> Dear Sven,
> >>>>>> 
> >>>>>> I have no direct experience of
> DATSCANs but I assume they are similar
> >>>>>> to general SPECT or PET
> scans.  We have had success registering
> >>>>>> SPECT/PET to MRI before.  It
> is always better to register the SPECT/PET
> >>>>>> to that subject's MRI using 6 DOF
> with FLIRT and a cost function like
> >>>>>> mutualinfo or normmi.  I
> would normally choose the best T1-weighted
> >>>>>> scan as the reference, but it may
> depend on what features are most
> >>>>>> clearly seen in your DATSCAN.
> >>>>>> 
> >>>>>> Once you've got a good
> registration of your DATSCAN to your MRI,
> >>>>>> then you can register the MRI to
> the MNI standard space image.
> >>>>>> This registration can be done with
> non-linear (FLIRT then FNIRT)
> >>>>>> whereas it is usually very, very
> bad to try and register the SPECT/PET
> >>>>>> with non-linear directly as there
> are very few features there to drive
> >>>>>> that registration.
> >>>>>> 
> >>>>>> When you have the two
> registrations then you can combine them with
> >>>>>> convertwarp to get a non-linear
> registration from the DATSCAN to
> >>>>>> the MNI standard space.
> >>>>>> 
> >>>>>> I do not know what you want in
> terms of a "specific template of the
> >>>>>> basal ganglia" but we have several
> atlases in FSL, and they include
> >>>>>> basal ganglia parcellations.
> >>>>>> 
> >>>>>> All the best,
> >>>>>>    Mark
> >>>>>> 
> >>>>>> 
> >>>>>> 
> >>>>>> On 16 Mar 2011, at 07:37, Sven
> Haller wrote:
> >>>>>> 
> >>>>>>> Dear all
> >>>>>>> 
> >>>>>>> I would like to normalize
> DATSCANs to MNI standard space
> >>>>>>> I also have 3DT1 (easy using
> FSLVBM) and DTI (easy using TBSS).
> >>>>>>> 
> >>>>>>> Are there any existing tools
> for FSL for DATSCANs?
> >>>>>>> Is there a specific template
> of the basal ganglia?
> >>>>>>> Any experience whether it is
> better to perform a linear registration DATSCAN to DTI, and
> then use the non-linear registration of TBSS, or better
> directly register DATSCAN to NMI? In that case, how? Linear
> or non-linear?
> >>>>>>> 
> >>>>>>> Any help is highly
> appreciated
> >>>>>>> 
> >>>>>>> Sven
> >>>>>>> 
> >>>>> 
> >>> 
> >> 
> >> 
> >> 
> >> -- 
> >> Dr. med. Cornelius J. Werner
> >> Department of Neurology
> >> RWTH Aachen University
> >> Pauwelsstr. 30
> >> 52074 Aachen
> >> Germany
> >> 
>