 |
 |
Dear Mark Again, a long, not relevant answer to my question. What about possible explanations related to probabilistic tractography and not related to corrected DTI data? From people who deal with probabilistic tractography every day Thank you Avner On 1/19/14 3:09 AM, "Mark Jenkinson" <[log in to unmask]> wrote: > Dear Avner, > > I am sorry that you were dissatisfied with my attempts to help you. I > genuinely try to help everyone that I can on the list. > > When working from only a few lines in an email it is hard to not make some > assumptions, but actually I do not like making assumptions and I try to avoid > them. I did assume that you work for the NIH (based on your email address and > sign-up name) and therefore were in contact with others in the NIH with > experience in diffusion imaging and analysis. It is a pity if you do not have > access to such people. > > I was not intending to imply that we could not provide you any information, > but the situation that you described, with unintuitive results in an > experiment with patients vs controls, requires very careful analysis and > scrutiny to avoid making incorrect interpretations. This scrutiny would be > beyond what we could provide in a few paragraphs of an email. Matt has > explained something about what tractography gives you and provided one > potential explanation, but as he points out himself there are other > possibilities and the interpretation is quite challenging. In your case I > think it is important to carefully investigate all potential factors that > could drive the results, such as image quality (e.g. SNR), artifacts > (including what remains after standard artifact correction), the > anatomy/geometry of the brain areas you are investigating, as well as the > biology of the particular pathologies involved. Given the many complex issues > that can arise here, related to diffusion imaging, brain anatomy and biology > (not just tractography), I recommended that you seek out someone who could > look carefully through your data and talk to you about issues related to the > data, the analysis, the anatomy and the biology involved in this particular > study. > > I still recommend that you seek someone out to discuss these issues, since we > cannot adequately cover these things by email. This is why I was suggesting > that you find someone in the NIH, but it would not have to be someone from > there. I make this recommendation because I honestly think it is important in > order to make sure that you get a correct interpretation of your study. If > you have very specific questions then we are happy to answer them, but I > strongly encourage you to find someone to discuss your study with in detail. > > As for the response from Tim Behrens, I hope that you can appreciate that > answering emails, writing documentation and textbooks is something that takes > away from research time and that each of us makes certain sacrifices in order > to do these things. We all have to decide on the nature and amount to which > we can undertake such tasks. If we do not limit this time then we would not > be able to do research, write papers and grants, and therefore stay employed. > I try to give advice on the list that I feel is of most benefit given the > limited time I have to answer such queries on what is quite an active email > list. I hope that you can respect this situation and can believe that my > emails were really intended to help, even if you were not happy with them. > > All the best, > Mark > > > > On 18 Jan 2014, at 13:30, "Meoded, Avner (NIH/NINDS) [E]" > <[log in to unmask]> wrote: > >> Dear Mark, >> >> I see you like to make assumptions. So let us assume that I am an high >> school student who does not understand a thing about DTI. Moreover I do not >> understand the basics of probabilistic tractography. So in order to >> understand more I read Diffusion MRI book (edited by Berg and Behrens) and >> also papers that deal with different tractography methods. So now I >> understand a little bit of tractography but still there are unclear issues >> that I would like to clarify with the experts in the field- that is the >> reason I contacted FSL community. >> If you see the title of my mail it is "Values in matrix1 after probtrackx"; >> The specific question I have is what those values mean? Probabilistic >> tractography aim to quantify uncertainty on the PDD and build a connectivity >> distribution. Now if you go and check matrix obtained from network1 option >> in probrackx2 you will see that the matrix contain values in the range of >> 1-1,000,000 and beyond. You mentioned in you last e-mail that: "Uncertainty >> in direction at any point in the brain will enhance the uncertainty in the >> tractography from that point onwards for any tracks that pass through that >> point." How can we learn about this uncertainty from the matrix values? >> >> Indeed at the NIH there are many experts who are always available for >> discussion about all aspects of health and science. However, is >> FSL/Probtrakcx a NIH application??? >> >> Finally I would like to show Timothy Behrens's response to my question : >> >> "if you have posted it to the FSL list then you should get an answer soon. >> It is a very effective community forum. You will understand that with more >> than 5000 users, there is no way I can personally answer every question and >> hope to maintain a research career!" >> >> This is the answer from the researcher who is the first author on the >> NeuroImage paper from 2007 about probabilistic tractography, and also the >> one who wrote the chapter MR diffusion tractography with Saad Jbadi in the >> book mentioned above. >> >> >> >> >> Avner >> >> >> On 1/18/14 4:58 AM, "Mark Jenkinson" <[log in to unmask]> wrote: >> >>> Hi, >>> >>> Artifact "correction" methods don't fully remove all artifacts, so you >>> cannot >>> rule out the possibility that artifacts are causing the things you are >>> seeing >>> just because you have run artifact correction. Such methods remove a lot of >>> the effect of artifacts but not absolutely everything. >>> >>> I'm not sure what you mean by "steps" but the samples in probtrack refer to >>> individual streamlines (that are selected from the probability distribution >>> of >>> possible streamlines). Uncertainty in direction at any point in the brain >>> will enhance the uncertainty in the tractography from that point onwards for >>> any tracks that pass through that point. >>> >>> You definite cannot make categorical statements such as "more samples >>> mean[s] >>> more disease". >>> As I said, there are a *lot* of things that can influence tractography >>> results >>> and you really should discuss you particular case, with your particular >>> subjects and you particular data acquisition, with someone who is >>> experienced >>> with tractography. There certainly should be such people in the NIH. >>> >>> All the best, >>> Mark >>> >>> >>> On 17 Jan 2014, at 13:10, "Meoded, Avner (NIH/NINDS) [E]" >>> <[log in to unmask]> wrote: >>> >>>> Hi >>>> The raw DTI data was corrected for artifacts. >>>> As you mentioned less uncertainty may enhance measures of connectivity. But >>>> in my case I documented reduced FA and not increased FA, the latter is seen >>>> perhaps in regions with reduced crossing fibers. >>>> Now my question is specific to probabilistic tractography: number of >>>> samples >>>> obtained from probtrackx between to regions mean number of "steps" track >>>> does; are those "steps" depends on the uncertainty? So at the end more >>>> samples mean more disease? >>>> >>>> Thank you >>>> >>>> Avner >>>> >>>> On 1/17/14 7:39 AM, "Mark Jenkinson" <[log in to unmask]> wrote: >>>> >>>>> Hi, >>>>> >>>>> These are not simple questions and it will depend a lot on the nature of >>>>> your >>>>> data - SNR, artefacts, amount of movement, etc. There are also some >>>>> potential >>>>> biological possibilities, such as reduction in crossing tracts, which can >>>>> enhance measures of connectivity (since there is less uncertainty in the >>>>> crossing region) without meaning that the axonal tract is biologically >>>>> "stronger". You should look very critically at your data and show it to >>>>> people who are experienced with diffusion analysis. >>>>> >>>>> All the best, >>>>> Mark >>>>> >>>>> >>>>> On 16 Jan 2014, at 18:08, "Meoded, Avner (NIH/NINDS) [E]" >>>>> <[log in to unmask]> wrote: >>>>> >>>>>> Dear FSL users >>>>>> >>>>>> I conducted a study with network1 option and then did structural >>>>>> connectome >>>>>> analysis, in patients affected with neurodegenerative disease. >>>>>> I also performed TBSS and found reduced FA values in different areas in >>>>>> patients compared to controls. >>>>>> The problem is that I have higher values stored in the connectivity >>>>>> matrices >>>>>> in patients compared to controls, and hence after connectome analyses I >>>>>> obtained networks that are more connected in patients. Now I know that >>>>>> these >>>>>> values cannot represent axons, but how you can explain reduced FA in >>>>>> patients >>>>>> and more streamlines evaluated in probtrackx? Or what are the numbers >>>>>> stored >>>>>> in the matrix mean? (after running seed to seed network 1) >>>>>> >>>>>> Is this because in patients (with white matter disease, lower FA) there >>>>>> is >>>>>> more uncertainty in voxels between roi1 and roi2 and therefore we get >>>>>> more >>>>>> samples so basically tracts tend to spread more and as a results more >>>>>> sample? >>>>>> so at the end more samples which represents more uncertainty (disease) >>>>>> Should I normalize the matrices in some way >>>>>> >>>>>> >>>>>> Thank you >>>>>> >>>>>> Avner