<div dir="ltr">Hi Romain,<div>Yes, that is correct, the first (ideal) approach would be to divide all DW and B=0 images by the mean CSF. For a recent AD study I actually used the 95th percentile of voxels within a CSF mask. Just to make sure I was not getting any PV with grey matter.</div><div><br></div><div>As Donald said, at typically DWI resolutions this can only be done with elderly populations. For cohorts below 60 years I normally use the median b=0 WM value. As Luis suggested, you could also use the average DWI signal. However, if your WM mask includes voxels affected by pathology (eg a reduced DW signal), then your normalisation will be biased and you may remove some of the effect you are looking for. The b=0 intensity can also be affected by disease and may bias your normalisation, however our assumption is that pathology induced changes to T2 are less severe than the DW signal. As long as the pathology is not global, then using the median value for normalisation means you are less likely to introduce a bias. When computing the median you could also mask out WM regions you suspect are affected by the disease. A good sanity check to ensure that you are not introducing a bias is to compare the median WM value across patient groups with a t-test (to make sure there is no difference).</div><div><br></div><div>We normally use N4 to estimate the bias field on the b=0 and apply it to the DW volumes. This seems to work OK, however we don't have really severe bias fields.</div><div><br></div><div>Just to follow up on what Donald mentioned regarding problems with dividing by the voxel b=0 in voxels with CSF partial volume. This is not just an issue for spherical deconvolution and Apparent Fibre Density, but also for tensor FA and ADC (see <a href="http://www.ncbi.nlm.nih.gov/pubmed/11323803">http://www.ncbi.nlm.nih.gov/pubmed/11323803</a>). </div><div><br></div><div>Cheers,</div><div>Dave</div><div><br></div><div><br></div><div><br></div><div><br></div><div> <br><div class="gmail_extra"><br><div class="gmail_quote">On 17 December 2014 at 02:23, Luis Concha <span dir="ltr"><<a href="mailto:lconcha@unam.mx" target="_blank">lconcha@unam.mx</a>></span> wrote:<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex"><div dir="ltr">I have used fsl's FAST to estimate the bias field on the b=0 and applied it to the DWIs and it seems to work well.<div><br></div><div>I guess one could also use some the segmentations provided by FAST to obtain the mean signal of WM voxels (of the average DWI) and use that to normalise the DWI signal between subjects.</div></div><div class="gmail_extra"><span class=""><br clear="all"><div><div><div dir="ltr">Dr. Luis Concha<br>Instituto de Neurobiología<br>Laboratorio C-13<br>UNAM, Campus Juriquilla<br>Boulervard Juriquilla 3001<br>Juriquilla, Querétaro.<br>C.P. 76230<br>México<br>Tel (442) 2 38 10 54<br>Fax (442) 2 38 10 46<br><a href="http://personal.inb.unam.mx/lconcha/" target="_blank">http://personal.inb.unam.mx/lconcha/</a><br></div></div></div>
<br></span><div><div class="h5"><div class="gmail_quote">On Tue, Dec 16, 2014 at 8:41 AM, romain valabregue <span dir="ltr"><<a href="mailto:romain.valabregue@upmc.fr" target="_blank">romain.valabregue@upmc.fr</a>></span> wrote:<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
<div bgcolor="#FFFFFF" text="#000000">
<div>Hello<br>
<br>
This is an interesting thread (worth to put on the wiki ... since
few people know that you do no take the B0 ...)<br>
<br>
Just to be sure I understand the first approach : you divide all
DWI volume by the mean csf value taken from the b=0 images ?<br>
<br>
What about about bias field correction <br>
The bias is a big concern to: it is very large with 32 channel
coils<br>
<br>
A few input on this ?<br>
<br>
N4 on the B0 and apply it to the DWI ? does it works well.<br>
<br>
Many thanks <br>
<br>
Romain<br>
<br>
<br>
Le 16/12/2014 14:00, J-Donald Tournier a écrit :<br>
</div><div><div>
<blockquote type="cite">
<div dir="ltr">Hi Luis,
<div><br>
</div>
<div>Well spotted. That is one of the issues that we still don't
have a totally satisfactory answer for. Basically, we need an
internal reference intensity for each subject so that we can
rescale their data to a comparable scale. One approach was to
use the CSF intensity, which works fine when the ventricles
are sufficiently large that you can get a clean estimate of
the CSF signal free from partial volume artefacts. While this
works in older subjects, it's difficult to do in younger
cohorts. Another approach that we use is to measure the b=0
signal within a conservative white matter mask, and use the
median or mean value as the reference intensity. This is
effect scales the data to a single, subject-specific, global
WM b=0 intensity, avoiding the issues introduced by voxel-wise
normalisation to the b=0 signal. In all cases, the primary
concern is whether the intensity used as a reference is
affected by the condition under investigation, and hence
whether this step may either mask a genuine effect or
introduce an effect that is not present in the DW data itself.
My guess is that the latter approach (normalisation to a
subject-specific global WM b=0 signal) raises the fewest
concerns since it's closest to what most people would naively
expect anyway (i.e. normalisation to the voxel-wise b=0
signal). </div>
<div><br>
</div>
<div>Happy to hear your thoughts...</div>
<div><br>
</div>
<div>Cheers,</div>
<div>Donald.</div>
<div><br>
</div>
<div><br>
</div>
</div>
<div class="gmail_extra"><br>
<div class="gmail_quote">On 15 December 2014 at 23:11, Luis
Concha <span dir="ltr"><<a href="mailto:lconcha@unam.mx" target="_blank">lconcha@unam.mx</a>></span>
wrote:
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
<div dir="ltr">This is a very interesting discussion, thanks
Rob and Donald for the detailed answers.
<div><br>
</div>
<div>Rob, you mention that for inter-subject studies you
would need</div>
<div>a) B1 field correction (presumably accomplished by N3
or N4 or similar tools), and</div>
<div>b) <span style="font-family:arial,sans-serif;font-size:13px">inter-subject
intensity normalisation.</span></div>
<div><span style="font-family:arial,sans-serif;font-size:13px"><br>
</span></div>
<div><font face="arial, sans-serif">If not using a b=0
singnal normalisation, how can we get signal units
comparable between individuals?</font></div>
</div>
<div class="gmail_extra"><br clear="all">
<div>
<div>
<div dir="ltr">Dr. Luis Concha<br>
Instituto de Neurobiología<br>
Laboratorio C-13<br>
UNAM, Campus Juriquilla<br>
Boulervard Juriquilla 3001<br>
Juriquilla, Querétaro.<br>
C.P. 76230<br>
México<br>
Tel (442) 2 38 10 54<br>
Fax (442) 2 38 10 46<br>
<a href="http://personal.inb.unam.mx/lconcha/" target="_blank">http://personal.inb.unam.mx/lconcha/</a><br>
</div>
</div>
</div>
<div>
<div>
<br>
<div class="gmail_quote">On Mon, Dec 15, 2014 at 7:18
AM, J-Donald Tournier <span dir="ltr"><<a href="mailto:jdtournier@gmail.com" target="_blank">jdtournier@gmail.com</a>></span>
wrote:<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
<div dir="ltr">Hi Jan,
<div><br>
</div>
<div>Just to expand a little further on what Rob
said, the main reason for not normalising to
the b=0 signal is essentially to preserve the
apparent fibre density. Really, the problem is
that normalising to the b=0 signal breaks the
linearity of the DWI signal to the FOD
(irrespective of the log transform), and that
is something we think should be avoided if at
all possible. This is an issue that I wish I'd
described explicitly in my original 2004
spherical deconvolution paper (even back then,
all the processing was done on the raw
signal)... As Rob mentioned, we'll try to
rectify this is a future paper, but for now,
here's a brief description of my reasons for
this.</div>
<div><br>
</div>
<div>This is based on a fundamental aspect of
spherical deconvolution and mixture models in
general: that the DWI signal scales <i>linearly</i> with
the amount of tissue present. While the
simulations done by Dave Rafflelt in the paper
Rob mentioned do make the point very nicely,
their purpose is a lot more specific than is
required for this argument. Basically, If a
voxel contains two fibre bundles, the signal
you measure is the sum of the signals for each
bundle individually (at least, it's modelled
as such). This however does not necessarily
hold for the signal <i>attenuation</i>, since
the b=0 signal is not uniform throughout the
brain. </div>
<div><br>
</div>
<div>Consider for example voxels containing
mixtures of WM & CSF. The b=0 signal for
CSF is typically very high relative to WM (due
to its long T2). If half the voxel contains
CSF, the other half WM, the b=0 signal for
that voxel would be essentially double what it
would be for pure WM (assuming CSF b=0 signal
is ~3x that of WM). On the other hand, the DW
signal for CSF is small, and to all intents
and purposes negligible at high b-values. This
means the <i>raw</i> DW signal would be what
you would expect to measure for a voxel
containing half the volume of WM, but the
signal attenuation would be halved again
(since the b=0 signal is double). So the
apparent relative volume fraction (fibre
density) derived using signal <i>attenuation</i>
would be ~a quarter that of pure WM, while
using the<i> raw</i> DW signal would give you
the correct answer: half that of pure WM. If
you care about being able to compare apparent
fibre densities across voxels in the presence
of large variations in the b=0 signal between
different tissue types (i.e. as you would
expect in the brain), you shouldn't normalise
to the b=0 image. </div>
<div><br>
</div>
<div>Note this isn't just about voxel-based
analysis of apparent fibre density or SIFT:
this is also important for example during the
tractography itself, since the termination
criteria are applied on the FOD amplitude
directly. It is also important for anything
that involves consistent scaling of the noise
(e.g. bootstrap analysis), since normalising
to the b=0 will also introduce large and rapid
spatial variations in the noise
characteristics of the data. There are many
facets to this issue, and I won't bother going
into them in any more detail here - I'll leave
that for the future paper Rob mentioned. But
in a nutshell, this is the reason MRtrix has
always operated on the raw DW signal, not its
attenuated version. </div>
<div><br>
</div>
<div>Hope this all makes sense.</div>
<div>Cheers,</div>
<div><br>
</div>
<div>Donald.</div>
<div><br>
</div>
</div>
<div class="gmail_extra"><br>
<div class="gmail_quote">
<div>
<div>On 15 December 2014 at 00:32, Robert
Smith <span dir="ltr"><<a href="mailto:robert.smith@florey.edu.au" target="_blank">robert.smith@florey.edu.au</a>></span>
wrote:</div>
</div>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
<div>
<div>
<div dir="ltr">Hi Jan,
<div><br>
</div>
<div>This is an important point, and
one that we sometimes forget that we
(as in, the MRtrix dev team) think
about quite differently to others in
Diffusion MR.</div>
<div>We will draw attention to this
issue in an upcoming publication,
but I'll try to give a succinct
explanation here.</div>
<div><br>
</div>
<div>Conventionally, the log-transform
with respect to the b=0 image
converts a signal amplitude to an
apparent diffusion coefficient;
nothing controversial here. However
if you were to then apply a
spherical deconvolution transform,
the FOD amplitude along a particular
direction would be proportional to
the ADC of the fibre population
oriented along that direction. This
isn't particularly useful
information; it doesn't tell us much
about differences between fibre
populations throughout the image, or
indeed within a voxel.</div>
<div><br>
</div>
<div>Ideally what we actually want for
a number of applications is the
volume of each fibre population
element, in all voxels throughout
the image. Based on David Raffelt's
early <a href="http://www.sciencedirect.com/science/article/pii/S1053811911012092" target="_blank">simulations</a>,
it turns out that (under certain
conditions) the radial component of
the DWI signal amplitude is actually
a pretty decent marker for
intra-cellular volume. Therefore, by
ignoring the b=0 images completely
and just running SD on the raw DWI
intensities, we get pretty useful
biological information and
interpretation from the FOD; we also
conveniently bypass the issue of
Gibbs ringing in the b=0 images.
Caveat is that you need a uniform B1
field (i.e. intensity bias field
correction); for applications like
AFD you also need inter-subject
intensity normalisation, but that's
not necessarily a problem for SIFT
depending on how you're using it.</div>
<div><br>
</div>
<div>That's all for now. Hope that
clarifies why we choose to apply SD
in this way; in fact, this approach
dates all the way back to the
original SD paper.</div>
<div>Rob</div>
</div>
<div class="gmail_extra"><br clear="all">
<div>
<div>
<div dir="ltr"><br>
--<br>
<br>
<span style="color:rgb(255,102,0)"><b>Robert
Smith, Ph.D</b><br>
Research Officer, Imaging
Division</span><br>
<br>
The Florey Institute of
Neuroscience and Mental Health<br>
Melbourne Brain Centre - Austin
Campus<br>
245 Burgundy Street<br>
Heidelberg Vic 3084<br>
Ph: <a href="tel:%2B61%203%209035%207128" value="+61390357128" target="_blank">+61 3 9035
7128</a><br>
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</div>
</div>
</div>
<div>
<div>
<br>
<div class="gmail_quote">On Sat,
Dec 13, 2014 at 1:37 AM, Jan
Schreiber <span dir="ltr"><<a href="mailto:schreiber@cbs.mpg.de" target="_blank">schreiber@cbs.mpg.de</a>></span>
wrote:
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">Dear
MRtrix Team,<br>
<br>
thank you very much for this
great software and for making
it freely<br>
available!<br>
<br>
In your publication "SIFT:
Spherical-deconvolution
informed filtering of<br>
tractograms" you state<br>
<br>
"The diffusion signal must not
be normalised to the b = 0
image<br>
intensity. This preserves the
linearity of the spherical
deconvolution<br>
transform between the measured
DW signal and the resulting
FOD."<br>
<br>
Shouldn't we preserve the
linearity of the spherical
deconvolution<br>
transform between the FOD and
the DW _signal attenuation_
rather than<br>
the DW _signal_?<br>
<br>
Thanks,<br>
Jan<br>
<br>
</blockquote>
</div>
</div>
</div>
</div>
<br>
</div>
</div>
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<div>
<div dir="ltr"><b><font color="#990000">Dr
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<div><font color="#990000"><br>
</font></div>
<i><font color="#990000">Senior
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Perinatal Imaging &
Health, 1<sup>st</sup> Floor
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-- <br>
<div>
<div dir="ltr"><b><font color="#990000">Dr J-Donald Tournier
(PhD)</font></b><br>
<div><font color="#990000"><br>
</font></div>
<i><font color="#990000">Senior Lecturer, </font></i><i><font color="#990000">Biomedical Engineering</font></i>
<div><i><font color="#990000">Division of Imaging Sciences
& Biomedical Engineering<br>
King's College London</font></i>
<div><i><font color="#990000"><br>
</font></i></div>
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of Perinatal Imaging & Health, 1<sup>st</sup> Floor
South Wing, St Thomas' Hospital, London. SE1 7EH</span><br>
</font></i></div>
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7118 ext 53613</font></i></div>
</div>
<div><i><font color="#990000"><b>W:</b> <a href="http://www.kcl.ac.uk/medicine/research/divisions/imaging/departments/biomedengineering" target="_blank">http://www.kcl.ac.uk/medicine/research/divisions/imaging/departments/biomedengineering</a></font></i><br>
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<br></blockquote></div><br clear="all"><div><br></div>-- <br><div class="gmail_signature"><div dir="ltr"><div><b><font color="#ff6600">David Raffelt (PhD)</font></b></div><div><font color="#ff6600">Post Doctoral Fellow</font></div><div><br></div><div>The Florey Institute of Neuroscience and Mental Health</div><div>Melbourne Brain Centre - Austin Campus</div><div>245 Burgundy Street</div><div>Heidelberg Vic 3084<div>Ph: <a value="+61390357024">+61 3 9035 7024</a></div></div><div><a value="+61390357024">www.florey.edu.au</a></div></div></div>
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