Hi Vincent - Problems 1-4 all look like head motion. Because the
acquisition of the slices is interleaved (all the odd slices are acquired
and then all the even slices are acquired), if the subject moves somewhere
in between, you'll see that the even slices are shifted with respect to
the odd slices. So you get this stripey look. (Horizontal stripes are
never flattering, especially on brains.)
The eddy/motion correction step will not solve this because it registers
each volume as a whole, so it will not move the slices with respect to
each other.
Even if tracula is unaffected by these issues (perhaps thanks to the prior
anatomical info that it uses) and the tracts look fine, the FA/MD/etc
values will be affected. (We've done some work on this that's currently in
review.) To begin with, you can check if these issues occur more often in
one of your groups than the other.
For either FA or the ball-and-stick model, I wouldn't go below 30
directions.
For problem 5, I don't see the spikes inside the brain, only in the
background, so you may be fine using that data set.
Hope this helps,
a.y
On Wed, 16 Oct 2013, Vincent Brunsch wrote:
Thank you so much, Anastasia!
Your comments help a lot and save a huge amount of time..
Indeed, I'm afraid, I have more questions.
Until now I have only done what you proposed in 3.
I observed 5 types of problems in a total of 12 (out of 78) time points:
The first is what you described: A dark line referring to one slice that is
much darker than its neighbors. I was happy to find this in only 1-2 volumes
of all.
The second is the same but the slices being only slightly darker than their
neighbors. I guess it's just up to me what to do here, just need to make a
decision. This happens more often.
The third is a distortion of a sequence of slices. It cannot be a movement
artifact (I think) because it is going back and forth with every slice. In
attached picture "1" you can clearly detect the type 1 problem (the dark
line) but also this third problem over almost the entire volume. It is as if
the slices were not properly aligned to each other there. This is the most
abundant problem type.
The fourth type of problem is similar to the first 3, only that the lines
don't go through the entire brain, which seems weird..I only detected this
once, see picture "2".
The last one is a background artifact that is visible in the z-axes, see
picture "3", I'm afraid it will mess up this scan completely..I also
detected this only once.
As I said, I was pretty happy in the beginning that I only saw these 1-2
volumes that were very dark. However, I also had a look at the dmri/dwi
files after the eddy and simple motion correction step and unfortunately all
of the mentioned problems persist. :( Especially concerning the third type
of problem this is really a pain.
So it seems, I have to remove a lot of volumes and/or need to take some of
the subjects completely out of our analysis. For this I would like to know:
When I remove 1,2..10, 20 volumes, how does this impact the calculations of
the tensor or the ball-and-stick parameters? I thought to find some
repetitions in the bvec-files but it seems there are really 60 unique
directions in our dwi-scans and I wonder why I can just remove one (or
more/how many per subject?).
Were problem types 3-5 reported by someone else before and can I do
something about them apart from removing the volumes?
On an additional note: I told you much earlier that I had to reinitialize
some tracts of some subjects as they were not at all or badly reconstructed.
However, this does not seem to correlate with these problems here so I
wonder if TRACULA maybe is not so much effected by these problems after all?
Thank you!
Vincent
Am 10/14/2013 5:12 PM, schrieb Anastasia Yendiki:
Hi Vincent,
3. It's a pain, isn't it? I sympathize but looking at the data is always a
good idea. Since you'll see all 3 views in fslview, the dark slices will
look like dark lines in two of these views, so you don't have to scroll
through slices. There's a couple of things you can do about motion, for
example you can remove the DWI volumes that have the artifacts. But you'll
have to make sure you're not doing this more for one group than the other.
2. What I usually look at is dlabel/diff/aparc+aseg.bbr.nii.gz, overlaid
on dmri/dtifit_FA.nii.gz. And yes, I do this for all subjects and yes, it
takes a while. Listening to music helps.
Let me know if you have more questions!
a.y
On Mon, 14 Oct 2013, Vincent Brunsch wrote:
Hi Anastasia!
I will go backwards with increasing difficulty to understand everything:
4. I see, yes this would not make sense. Thank you for the explanation!
3. With fslview I will have to run through 393,120 slices, then. (72 slices
in z-direction for our 70 DWI scans for tp1 and tp2 for each of our 39
subjects) I will go dwi image by dwi image running through the 72 slices
rather fast. Just to make sure I am not wasting a lot of time: is this what
I
should do? If I detect slices that are much darker than their neighbors, wil
l
I need to exclude this subject for the analysis or can I do something about
it?
2. Yes, I use bbregister and I also use the anatomical T1 weighted scan to
extract the brain mask (usemaskanat=1). To make sure that everything is
alright, I would go slice by slice in tkmedit with
tkmedit [subject] brainmask.mgz -surfs -aparc+aseg where [subject] would be
the base AND both longitudinal runs. I understand that I need to check if
white matter is where it should be, if the cortical and pial surfaces are
where they should be and if the labelling is correct. Again, as this will
take probably even longer than 3. I would like to make sure this is the righ
t
thing to do before starting the quality check.
Thanks again!
Vincent
Am 10/11/2013 2:13 PM, schrieb Anastasia Yendiki:
Hi Vincent - I'll take on the tracula-related parts:
2. For tracula, the part of the recon-all output that matters is the
aparc+aseg. The surfaces will play a role only the DWI-to-T1 registration
(assuming you opt to use bbregister).
3. It's important to check your DWI data for obvious motion artifacts,
(slices that are much darker than their neighbors). Right now this has to
be done visually, but it's on my list to produce some motion metrics as
part of the preprocessing.
4. The ball-and-stick model (that bedpostx fits to your data) is used by
the tractography algorithm in tracula, but there are no stats produced on
the parameters of that model currently. That's something that can be added
in the future as well. Note though that it wouldn't make sense to just
average f1 or f2 over the pathway, because compartment 1 in one voxel may
correspond to compartment 2 in some other voxel.
Hope this helps,
a.y
On Fri, 11 Oct 2013, [email protected] wrote:
Dear Freesurfer experts,
I want to do a quality check on our imaging data. I used the longitudinal
stream for SBA and as the first step for the longitudinal white matter
analysis with TRACULA.
We had two time points in our study and thus, in the freesurfer output
directory there are 5 folders per subject (2 cross-sectional runs, 2 long
runs and the base).
1. Would you recommend to use (all of) the QA_TOOLS on all of these 5
folders per subject for the SBA?
2. Independent of the previous question, for the longitudinal version of
TRACULA would you recommend to use (all of) the QA_TOOLS on the freesurfer
base folder only / additional folders?
3. In addition to the late visual check for well reconstructed pathways
with freeview, is there another automated possibility to check the quality
of the diffusion weighted images beforehand/do you think this is
necessary?
4. On another note: If I understand correctly, in TRACULA bedpostX is used
to reconstruct the pathways but then the mean over the voxels that were
hit (by the MCMC sampling of the paths) of measures from the tensor model
are taken as outputs. I wonder, is there also the possibility of using the
partial volumes f1, f2,.. as output measures?
Best,
Vincent
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