Dear MRtrix experts,
I am writing you to understand how it could be approached an issue with Fixel Based Analysis, I would be grateful if you could help.
The authors of this paper Conduction velocity, G-ratio, and extracellular water as microstructural characteristics of autism spectrum disorder were able to use FCD from FBA and T1w/T2w ratio to create a map with voxels values representing conduction velocity. Assuming whole brain tractography has been already performed with a certain parcellation, finding the weight and tract_length matrix (nr of streamlines connecting two regions & their mean length), and assuming we have the value of the conduction velocity in each voxel: how could I create the matrix of the conduction velocity according to the same parcellation used in the tractography (where each element represents the conduction velocity of the streamlines connecting the two regions)? Could any command already available in MRtrix be used for this purpose? Any other suggestion would be greatly appreciated.
Thanks in advance,
Mik
Dear all,
I thought I was not clear enough, so would like to reformulate.
Assuming I have the average conduction velocity in each voxel, would it be possible to calculate the average value along streamlines connecting two regions of the parcellation? I assume it could be sort of integral along the streamline.
Any suggestion would be appreciated,
Mik
Hi @michefabb,
I guess what you are trying to achieve is the connectome velocity-weighted or something like that, right?
In that case, first of all, you need to have your tractogram, velocity map and ROIs corregistered. Then, the following two command line will generate the matrix you are looking for:
tcksample tracks.tck Velocity.mif mean_Velocity_per_streamline.csv -stat_tck mean
tck2connectome tracks.tck nodes.mif mean_Velocity_connectome.csv -scale_file mean_Velocity_per_streamline.csv -stat_edge mean
This will generate a matrix where the value of connectivity is the “mean velocity”. I hope this helps.
Best regards,
Manuel
Thank you very much @mblesac for your kind reply. Yes, it is exactly what I would like to achieve and these commands look perfect!
I would have a couple of questions.
1- If I created the weight and length connectomes using tcksift2, I assume I should add the option -tck_weights_in weights.txt to the tck2connectome command, becoming:
tcksample tracks.tck Velocity.mif mean_Velocity_per_streamline.csv -stat_tck mean
tck2connectome tracks.tck nodes.mif mean_Velocity_connectome.csv -scale_file mean_Velocity_per_streamline.csv -stat_edge mean -tck_weights_in weights.txt
2- With reference to the MRtrix documentation about tck2connectome https://mrtrix.readthedocs.io/en/latest/reference/commands/tck2connectome.html I found a similar explanation to create a connectome matrix of “mean FA” and it states
firstly, for each streamline, the value of the underlying FA image is sampled at each vertex, and the mean of these values is calculated to produce a single scalar value of “mean FA” per streamline
I am unsure about what it is intended with “vertex”…does it mean that it is sampled at each point in which the streamline is split (if the streamline consists of 1000 points, it is sampled in all of them), or does it mean that it is sampled only at the initial and final points of the streamline (using ACT these would be only the GM/WM interfaces at the extremities of the streamline)?
Thanks again for your support!!
Mik
Hi,
I reply to the questions one by one:
1.- The commands look correct. However, the interpretation may be slightly different as now you are not calculating the mean, you calculate the weighted mean. See the full explanation here.
2.- My understanding is the first option, that it is sampled at every “step” of the streamline. I imagine that the usage of ACT + sampling only at the ends will give, for example, very low values in the FA-weighted connectome. But I don’t know for sure the answer.
I hope this helps.
Best regards,
Manuel
Thanks again @mblesac , I will try as you suggested!
Appreciated your help!