[Mristudio-users] DTI method: VBA, MRIstudio vs. TBSS

Fri May 14 13:41:19 EDT 2010

Dear Susumu Mori,

Thanks very much for your answer, it's very informative!
One question is that when you mention granularity and anatomy, it finally
all leads to the advantages of TBSS, the skeleton. so my answer looks a bit
repeated for a same point. Another one is I do need to find some flaw in
TBSS for defence use :P, so I find some limitation from the original paper.
BTW, I am NOT familiar with TBSS.
http://sirl.stanford.edu/~bob/pdf/DTI/Methods/Smith_TBSS_NeuroImage06.pdf

Finally, I arranged some defences based on your comments below. Have a look
if interested , or simply skip it :)

Thanks again & Best Wishes,
Gao

It has been quite a time since VBA was popularly used in DTI data, while
track-based spatial statistical gains popularity rapid in recent years. To
compare the two methods, there two points of views need to the clarified:

1.       Granularity. It represents the extent to which a system is divided
into smaller parts. In VBA, the brain is broken into nearly one million of
voxels, then it is normalized before comparing with one another. In
MRIstudio, it can superimpose the parcellation map and divided the brain
into 150 areas, thus it has less granularity than VBA (1 million vs. 150).
Whereas TBSS re-registers nearby voxels to the skeleton of white matter,
reduces the granularity and increases the accuracy of registration.

2.       Anatomy. In VBA analysis, computer algorithm registers the voxels
automatically, without considering any anatomical information. Another new
method of Tissue-specific, smoothing-compensated (T-SPOON) can improve the
tissue specificity in VBA method and compensation for images smoothing. TBSS
can also apply some anatomical information, i.e., the skeleton of white
matter, thus the registration would be better than totally automatic VBA
method.

TBSS definitely has its advantages in DTI analysis, nonetheless, it is not
without flaw or limitation: 1.Partial volume effect still exists in TBSS
method, and the problem may be greatly exacerbated in spatial smoothing; 2.
Increased head motion can increase image blurring and bias FA value; 3. In
regions of crossing tracts or junctions, TBSS may misinterpret the change of
tracks in junction as apparently reduced FA; 4. Finally, in patients with
apparent pathological changes, TBSS may exclude the areas from analysis.

There are always advantages and disadvantages of each method in DTI studies.
TBSS as new method, may be generally more accurate than VBA method, although
it needs more sophisticated data projection approach in the future. We also
need to keep in mind that DTI is based on information of water diffusion, it
may help to screen and generate hypothesis rather than to draw a final
conclusion.

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On 13 May 2010 23:44, susumu mori <susumu at mri.jhu.edu> wrote:

> Good question Gao.
>
> Here is my thought (my personal opinion, of course);
>
> 1) you are comparing VBA and TBSS. These are methods to "define
> corresponding pixels (or areas) across subjects", so that you can compare
> pixel numbers such as FA and MD among different brains. This is called
> "registration".
> 2) These methods can be classified from different point of views;
> 2-1) granularity: One extreme is to define the entire brain as one ROI. You
> can get the whole brain volume, whole brain FA, or whole brain histogram.
> While there is not much use of this approach, it is precise (do 10 times and
> you get the same results) and accurate (nobody makes mistakes about where is
> the whole brain except for some ambiguity about where you cut the ROI in the
> brainstem). The other extreme is the pixel, which is the smallest unit. This
> mean, you identify the corresponding pixels across subjects. Once you map
> the entire 1 million pixels in one brain to the other, it is the same as
> transforming one brain to the other (two brains now have the same shape).
> This approach is called "normalization" and, of course, not accurate because
> it is not possible to completely solve the system and accurately map all 1
> million pixels. VBA and TBSS are based on this normalization procedure.
> There are methods to ameliorate this accuracy issue. Usually VBA uses
> filters to blur the information. In my understanding, TBSS "re-register"
> nearby pixel information to the core of the white matter, which could be
> considered as a sort of filtering, reducing the granularity and hopefully
> increasing the accuracy.
> 2-2) Anatomy: When we do normalization, computer algorithm do not care
> about anatomy. It just does whatever it thinks best to register pixels. This
> is the pixel-based analysis. On the other hand, manual ROI is usually based
> on anatomical information we can perceive. This is anatomy-based analysis.
> Tractography-based analysis can also be considered as a kind of registration
> method. We do, for example, tractography of the cortico-spinal tract in 10
> subjects. Then we can define a group of pixels that belong to the CST and
> compare the pixel values. In this way, we define a specific area across
> subjects based on anatomy.
> 3) In MriStudio, DiffeoMap does pixel-based registration just as VBA. You
> can do VBA analysis. In addition, you can superimpose our parcellation map
> and divide the brain into about 150 areas. In terms of granularity, it is
> much less than VBA (more than 1 million pixels vs 150 areas). This is also a
> conversion to pixel-based to anatomy-based analysis.
> 4) Now going back to your question, VBA and TBSS are looking at the same
> data with different point of view. First of all, the granularity is
> different; TBSS reduces the information to the white matter core. Also, VBA
> is completely pixel-based but TBSS, which is not completely anatomy-based
> but has some anatomy-based factors by reducing the information to the core
> of the white matter.
> 5) In my opinion, all methods described above have advantages and
> disadvantages. I don't think any one of them is better than the other.
> Quantification based on location information is definitely one of the most
> difficult problems we are all facing.
> 6) On the other hand, your reviewer is correct, in a sense that it is
> always important to compare different results to enrich your data and
> interpretation. This is especially true if there is a tool widely used like
> TBSS. However, it is not like, one method should be treated as the gold
> standard and other approaches should give a similar result. If you compare
> VBA and TBSS, you likely to get different results because as explained above
> they are operating at the different granularity, precision, and accuracy.
> MRI image anlaysis is very often a screening and hypothesis generating tool
> rather than a tool to draw a conclusion. We are simply looking at 6MB
> information based on water signal.
>
> So, in conclusion,
>
> > No, VBA is not out of date
> > Yes, it is a good idea to compare results from widely used tools, but any
> normalization-based method should not be considered as a gold standard in my
> opinion. We just have to understand how they operate and what are their
> advantages and disadvantages.
>
>   On Thu, May 13, 2010 at 8:07 AM, lion gao <gaolion at gmail.com> wrote:
>
>>   Dear Experts,
>>
>>
>>
>> I have one part of my thesis on DTI data analysis. The method I used is
>> the voxel-based analysis (VBA) and I tried MRIstudio as well. One of the
>> examiners pointed out that track-based spatial statistics (TBSS), as a state
>> of art way, should have been considered.
>>
>>
>> I am familiar with TBSS, only know that it may reduce systemic
>> mis-registration inVBA and increasing papers published with the method. I am
>> not sure whether:
>> 1. VBA has become “out of date”,
>> 2. and TBSS has become a “golden standard” for DTI data analysis.
>>
>> Can someone help to justify the situation or defense a little bit? Thank
>> you very much in advance!
>>
>>
>> Best wishes,
>>
>> Gao
>>
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