[Mrtrix-discussion] SIFT: normalise to the b0 image

Tue Dec 16 05:00:19 PST 2014

Hi Luis,

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).

Happy to hear your thoughts...

Cheers,
Donald.

On 15 December 2014 at 23:11, Luis Concha <lconcha at unam.mx> wrote:
>
> This is a very interesting discussion, thanks Rob and Donald for the
> detailed answers.
>
> Rob, you mention that for inter-subject studies you would need
> a) B1 field correction (presumably accomplished by N3 or N4 or similar
> tools), and
> b) inter-subject intensity normalisation.
>
> If not using a b=0 singnal normalisation, how can we get signal units
> comparable between individuals?
>
> Dr. Luis Concha
> Instituto de Neurobiología
> Laboratorio C-13
> UNAM, Campus Juriquilla
> Boulervard Juriquilla 3001
> Juriquilla, Querétaro.
> C.P. 76230
> México
> Tel (442) 2 38 10 54
> Fax (442) 2 38 10 46
> http://personal.inb.unam.mx/lconcha/
>
> On Mon, Dec 15, 2014 at 7:18 AM, J-Donald Tournier <jdtournier at gmail.com>
> wrote:
>
>> Hi Jan,
>>
>> 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.
>>
>> This is based on a fundamental aspect of spherical deconvolution and
>> mixture models in general: that the DWI signal scales *linearly* 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 *attenuation*,
>> since the b=0 signal is not uniform throughout the brain.
>>
>> 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 *raw* 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 *attenuation* would
>> be ~a quarter that of pure WM, while using the* raw* 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.
>>
>> 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.
>>
>> Hope this all makes sense.
>> Cheers,
>>
>> Donald.
>>
>>
>> On 15 December 2014 at 00:32, Robert Smith <robert.smith at florey.edu.au>
>> wrote:
>>
>>> Hi Jan,
>>>
>>> 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.
>>> We will draw attention to this issue in an upcoming publication, but
>>> I'll try to give a succinct explanation here.
>>>
>>> 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.
>>>
>>> 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 simulations
>>> <http://www.sciencedirect.com/science/article/pii/S1053811911012092>,
>>> 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.
>>>
>>> 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.
>>> Rob
>>>
>>>
>>> --
>>>
>>> *Robert Smith, Ph.D*
>>> Research Officer, Imaging Division
>>>
>>> The Florey Institute of Neuroscience and Mental Health
>>> Melbourne Brain Centre - Austin Campus
>>> 245 Burgundy Street
>>> Heidelberg Vic 3084
>>> Ph: +61 3 9035 7128
>>> Fax: +61 3 9035 7301
>>> www.florey.edu.au
>>>
>>> On Sat, Dec 13, 2014 at 1:37 AM, Jan Schreiber <schreiber at cbs.mpg.de>
>>> wrote:
>>>>
>>>> Dear MRtrix Team,
>>>>
>>>> thank you very much for this great software and for making it freely
>>>> available!
>>>>
>>>> In your publication "SIFT: Spherical-deconvolution informed filtering of
>>>> tractograms" you state
>>>>
>>>> "The diffusion signal must not be normalised to the b = 0 image
>>>> intensity. This preserves the linearity of the spherical deconvolution
>>>> transform between the measured DW signal and the resulting FOD."
>>>>
>>>> Shouldn't we preserve the linearity of the spherical deconvolution
>>>> transform between the FOD and the DW _signal attenuation_ rather than
>>>> the DW _signal_?
>>>>
>>>> Thanks,
>>>> Jan
>>>>
>>>>
>>> _______________________________________________
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>>>
>>>
>>
>> --
>> *Dr J-Donald Tournier (PhD)*
>>
>> *Senior Lecturer, **Biomedical Engineering*
>>
>> *Division of Imaging Sciences & Biomedical EngineeringKing's College
>> London*
>>
>>
>> *A: Department of Perinatal Imaging & Health, 1st Floor South Wing, St
>> Thomas' Hospital, London. SE1 7EH*
>> *T: +44 (0)20 7188 7118 ext 53613
>> <%2B44%20%280%2920%207188%207118%20ext%2053613>*
>> *W: http://www.kcl.ac.uk/medicine/research/divisions/imaging/departments/biomedengineering
>> <http://www.kcl.ac.uk/medicine/research/divisions/imaging/departments/biomedengineering>*
>>
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-- 
*Dr J-Donald Tournier (PhD)*

*Senior Lecturer, **Biomedical Engineering*

*Division of Imaging Sciences & Biomedical EngineeringKing's College London*

*A: Department of Perinatal Imaging & Health, 1st Floor South Wing, St
Thomas' Hospital, London. SE1 7EH*
*T: +44 (0)20 7188 7118 ext 53613*
*W: http://www.kcl.ac.uk/medicine/research/divisions/imaging/departments/biomedengineering
<http://www.kcl.ac.uk/medicine/research/divisions/imaging/departments/biomedengineering>*
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