Well, I didn't mean TBSS was better than the other. Different granularity means different sensitivity/specificity to different types of diseases.<br><br>For example, when we are studying brain growth and tissue atrophy in certain neurodegenerative disease, it happens in a global manner. There is an overall tendency like frontal lobe develop earlier than the occipital lobe. When you are going after this type of changes, it doesn't make sense to use the smallest granularity (pixel). If the change is only 5%, you can't find it by pixel-based methods because each pixel is too noisy. TBSS may also have too much granularity because each skeleton point may average only few adjacent pixels. In this case, an ROI drawn in the frontal lobe and occiptal lobe averaging thousands of pixels may be a better method.<br>
<br>On the other hand if a lesion is sharply localized, then you want higher granularity. Pixels averaging always have a danger that abnormal pixels are averaged with normal pixels and thus dilute the effect.<br><br>Raw pixel-based data is therefore always nice to have. It has low sensitivity and you can hardly get any statistical level once you do multiple-pixel comparison. But if you lower the statistical thresholding, you start to see some tendency. The filtering (pixel averaging) by TBSS may help to bring up such information above the surface of statistical power. However, you can also argue that if the abnormality is localized to one side of the tract, the projection to the center of the white matter core would decrease the sensitivity. <br>
<br>Also, you can also argue that the skeletanization is somewhat a blackbox operation. When you are looking at the white matter away from the core where there are cross-subject variability, I'm not sure how the white matter is skeletanized and how they are aligned among subjects.<br>
<br>Again, VBA data is one step closer to raw data before the high order image analysis such as TBSS do something on the pixel-by-pixel data. So you can argue that VBA and TBSS is not A or B, it is more like A or AxB<br><br>
Hope it helps.<br><br><div class="gmail_quote">On Fri, May 14, 2010 at 1:41 PM, lion gao <span dir="ltr"><<a href="mailto:gaolion@gmail.com" target="_blank">gaolion@gmail.com</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;"><div>Dear Susumu Mori,</div>
<div> </div>
<div>Thanks very much for your answer, it's very informative!</div>
<div>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. </div>
<div><a href="http://sirl.stanford.edu/%7Ebob/pdf/DTI/Methods/Smith_TBSS_NeuroImage06.pdf" target="_blank">http://sirl.stanford.edu/~bob/pdf/DTI/Methods/Smith_TBSS_NeuroImage06.pdf</a></div>
<div> </div>
<div>Finally, I arranged some defences based on your comments below. Have a look if interested , or simply skip it :) </div>
<div> </div>
<div>Thanks again & Best Wishes,</div>
<div>Gao</div>
<div> </div>
<div>
<p class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman">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:</font></span></p>
<p class="MsoNormal" style="margin: 0cm 0cm 0pt; text-indent: 0cm;"><font face="Times New Roman"><span lang="EN-US"><span><font size="3">1.</font><span style="font: 7pt 'Times New Roman';"> </span></span></span><span lang="EN-US"><font size="3">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.</font></span></font></p>
<p class="MsoNormal" style="margin: 0cm 0cm 0pt; text-indent: 0cm;"><font face="Times New Roman"><span lang="EN-US"><span><font size="3">2.</font><span style="font: 7pt 'Times New Roman';"> </span></span></span><span lang="EN-US"><font size="3">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. </font></span></font></p>
<p class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman"> </font></span></p>
<p class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman">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.</font></span></p>
<p class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman"> </font></span></p>
<p class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman">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.</font></span></p>
<p class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman"></font></span> </p>
<p class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman"></font></span> </p>
<p class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman"></font></span> </p>
<p class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman">-------------------------------------------------------------------------------</font></span></p></div>
<div> </div>
<div><br><br></div>
<div class="gmail_quote">On 13 May 2010 23:44, susumu mori <span dir="ltr"><<a href="mailto:susumu@mri.jhu.edu" target="_blank">susumu@mri.jhu.edu</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0px 0px 0px 0.8ex; padding-left: 1ex;">Good question Gao.<br><br>Here is my thought (my personal opinion, of course);<br><br>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". <br>
2) These methods can be classified from different point of views;<br>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.<br>
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.<br>
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.<br>
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.<br>
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.<br>
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.<br>
<br>So, in conclusion, <br><br>> No, VBA is not out of date<br>> 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.<br>
<br>
<div class="gmail_quote">
<div>
<div></div>
<div>On Thu, May 13, 2010 at 8:07 AM, lion gao <span dir="ltr"><<a href="mailto:gaolion@gmail.com" target="_blank">gaolion@gmail.com</a>></span> wrote:<br></div></div>
<blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">
<div>
<div></div>
<div>
<p class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman">Dear Experts,</font></span></p>
<p class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman"> </font></span></p>
<p class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman">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. </font></span></p>
<p class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman"> </font></span></p>
<div class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman">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: </font></span></div>
<div class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman">1. VBA has become “out of date”, </font></span></div>
<div class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman">2. and TBSS has become a “golden standard” for DTI data analysis. </font></span></div>
<div class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman"></font></span> </div>
<div class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman">Can someone help to justify the situation or defense a little bit? </font></span><span lang="EN-US"><font size="3" face="Times New Roman">Thank you very much in advance! </font></span></div>
<div class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman"></font></span> </div>
<p class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman">Best wishes,</font></span></p>
<p class="MsoNormal" style="margin: 0cm 0cm 0pt;"><span lang="EN-US"><font size="3" face="Times New Roman">Gao</font></span></p><br></div></div>_______________________________________________<br>Mristudio-users mailing list<br>
<a href="mailto:Mristudio-users@mristudio.org" target="_blank">Mristudio-users@mristudio.org</a><br><a href="http://lists.mristudio.org/mailman/listinfo/" target="_blank">http://lists.mristudio.org/mailman/listinfo/</a><br>
Unsubscribe, send a blank email to: <a href="mailto:Mristudio-users-unsubscribe@mristudio.org" target="_blank">Mristudio-users-unsubscribe@mristudio.org</a><br><br></blockquote></div><br><br>_______________________________________________<br>
Mristudio-users mailing list<br><a href="mailto:Mristudio-users@mristudio.org" target="_blank">Mristudio-users@mristudio.org</a><br><a href="http://lists.mristudio.org/mailman/listinfo/" target="_blank">http://lists.mristudio.org/mailman/listinfo/</a><br>
Unsubscribe, send a blank email to: <a href="mailto:Mristudio-users-unsubscribe@mristudio.org" target="_blank">Mristudio-users-unsubscribe@mristudio.org</a><br><br></blockquote></div><br>
<br>_______________________________________________<br>
Mristudio-users mailing list<br>
<a href="mailto:Mristudio-users@mristudio.org" target="_blank">Mristudio-users@mristudio.org</a><br>
<a href="http://lists.mristudio.org/mailman/listinfo/" target="_blank">http://lists.mristudio.org/mailman/listinfo/</a><br>
Unsubscribe, send a blank email to: <a href="mailto:Mristudio-users-unsubscribe@mristudio.org" target="_blank">Mristudio-users-unsubscribe@mristudio.org</a><br>
<br></blockquote></div><br>