<div dir="ltr">Hi James,<div>Just to clarify, do you mean you extract a single peak with the largest amplitude within each voxel? Then normalise by the max amplitude across all voxels and subjects? If so, one potential issue is that the largest peak in corresponding voxels across subjects is not guaranteed to belong to the same fibre bundle. Also, during pathology you might see a decrease in the FOD peaks of one fibre, such that they are no longer the dominant peak in that region (and therefore are excluded from your analysis). <br>
</div><div><br></div><div>Simulations suggest the AFD along a given direction is proportional to the intra-axonal volume of axons aligned with that direction (at least with high b-values and long gradient pulse durations). Using lower b-values means that the AFD is also dependent on the signal from hindered extra-axonal water. And therefore the interpretation of any AFD group differences is not as clear cut. </div>
<div><br></div><div>The peak AFD amplitude is probably not a bad estimate of the total intra-axonal volume of axons belonging to the respective FOD lobe. However, inter-subject differences in fibre curvature (in subject space) will influence the peak (due to a difference in the spread of the FOD lobe). A better measure would be to use the integral of each FOD lobe. Rob uses the integral for his SIFT method, and I'm presenting a new tractography-based statistical method that uses the AFD integral at ISMRM next month.<br>
</div><div><br></div><div>One other issue is related to transforming the AFD peak amplitudes into template space. Modulation needs to be applied when spatially normalising any DWI measure representative of the restricted intra-axonal water fraction of a specific fibre population (whether it is the AFD peak, integral, or partial volume fractions computed using other methods, e.g. Behren's Ball and Stick model or Assaf's CHARMED). As discussed in the AFD paper, non-linear transformations may alter the width of a fibre bundle, and therefore modulation is needed to preserve the total intra-axonal volume of axons passing through any given cross-section of a fibre bundle. </div>
<div><br></div><div>Are you computing FODs using a single group-average response function for all subjects? To do AFD analysis you also must account for intensity variation across scans. Due to patient- and scan-specific scanner calibrations, the magnitude of the MR signal across different scans is not comparable. One way to account for this is to intensity normalise the DW images using some reference point. Ideally, the median CSF b=0 signal would be a good reference since it is unlikely to vary during pathology. However, at the current DWI resolution it is often hard to get a clean partial-volume-free estimate of the CSF, particularly in young patient groups. Alternatively you could use the median b=0 signal from brain parenchyma, however this is not ideal since it might be affected by the pathology being investigated. </div>
<div>The other way to account for scan intensity variation is to perform CSD using a subject-specific response function, however this is less robust and you might reduce your power to detect AFD differences due to larger group variation, or the possibility of pathology affecting voxels used to estimate the response function.</div>
<div><br></div><div>Just to clarify, the max_amp metric represents the amount of diffusion in the peak direction only for diffusion orientation distributions dOFDs (i.e those computed by Q-ball and DSI). Whereas FODs model the intra-axonal volume of fibres as a function of orientation. The amplitude of so-called "model free" diffusion ODFs is less informative, since it is impossible to tease out the contribution from multiple underlying fibre populations without some type of model (which in the case of spherical deconvolution is the response function).<br>
</div>
<div><br></div><div>Also, the peak FOD amplitude is more akin to the apparent<i> radial</i> diffusivity of the respective fibre population (and not the axial diffusivity as you suggest). Pathology-induced changes to restriction are more likely to influence the DW signal along radial orientations (especially at high b-values where the axial DW signal is non-existent). A decrease in the radial DW signal will present as a decrease in AFD along the fibre direction, and an increase in the radial diffusivity. Although I should warn against thinking of AFD in terms of radial diffusivity, since thinking in terms of diffusivity is clearly not a good way of looking at the DW signal arising from a <i>restricted</i> diffusion environment.<br>
</div><div><br></div><div>Since I'm on a roll, I might as well mention that TBSS is not ideal for doing 'whole brain' voxel-based analysis. Aside from the fact that it does not really analyse all brain voxels, projecting your measure of interest onto a skeleton based on the highest FA is problematic in crossing-fibre regions.<br>
</div><div><br></div><div style>In terms of doing AFD analysis in the future, we are hoping to release the tools as part of the next major MRtrix release, however this will depend on how much free time I have in the coming months.</div>
<div style><br></div><div style>Cheers,</div><div style>Dave</div><div><br></div><div style><br></div>
<div><br></div><div><br></div><div><br></div><div><br></div><div><br></div>
<div><div></div></div><br><div class="gmail_quote">---------- Forwarded message ----------<br>From: <b class="gmail_sendername">James Cole</b> <span dir="ltr"><<a href="mailto:james.cole@ucl.ac.uk" target="_blank">james.cole@ucl.ac.uk</a>></span><br>
Date: 15 March 2013 04:28<br>Subject: [Mrtrix-discussion] FOD amplitude<br>To: <a href="mailto:mrtrix-discussion@www.nitrc.org" target="_blank">mrtrix-discussion@www.nitrc.org</a><br><br><br>
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Dear MRtrixers,<br>
I've been using mrtrix for various things and came up with an
approach that I wanted to run by the experts. It might be that I'm
barking up entirely the wrong tree, so could use some guidance.
Regarding voxelwise metrics derived from the spherical deconvolution
(I saw the apparent fibre density (AFD) paper and this is something
I'd be interested in trying in the long run), I wondered whether the
largest FOD lobe might be sensitive to pathology. Here's my
analysis:<br>
<br>
Having run CSD (Lmax = 6, the b-value is only 1000, 42 directions)
on my data, I used find_SH_peaks, dir2amp and FSL's fslroi to
extract the FOD of the largest amplitude (I called this max_amp) and
thus was able to generate voxelwise max_amp maps per subject, in
native space. <br>
<br>
I then normalised the max_amp maps (by dividing by 3.5, to give a
scalar in the 0-1 range), having assessed the maximum amplitude in
any voxel across all subjects (which was 3.51ish). The idea being
that the the scalar now represents a score based on the amplitude of
the FOD lobe relative to the highest possible amplitude in vivo
tissue; thus 0 = absence of FOD and 1 = maximum possible FOD
amplitude.<br>
<br>
These normalised max_amp maps were then warped into group space
using the warps calculated from generating a groupwise template from
FA maps. I then created a mask using a threshold of FA>0.2 (to
limit analysis to white matter) and finally ran some stats (using
FSL randomise as per TBSS). In a group of 10 controls and 15
patients there were a number of significant clusters of increased
max_amp in controls, roughly corresponding to the corticospinal
tract and corona radiata. There were no increases in patients. <br>
<br>
The rationale behind this comes from the idea that the max_amp
metric represents the amount of diffusion in the principle
direction, but uncontaminated by crossing fibre effects (so perhaps
a 'better' version of axial diffusivity, I suppose). I'm not
assuming this idea is original by any means, perhaps just the
implementation of it in mrtrix.<br>
<br>
Apologies for the long post, but I'd be really appreciative of some
expert opinions. Any ideas for theoretical / practical improvements,
or reasons why this might not be representing what I think it is
would be most helpful.<br>
<br>
Many thanks,<br>
James<span><font color="#888888"><br>
<br>
<div>-- <br>
<b>James Cole PhD | Research Associate | Huntington's Disease
Research Group | UCL Institute of Neurology</b></div>
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<br></div><br><br clear="all"><div><br></div>-- <br><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>
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