Could Someone Provide Advice on the Optimal Pathway for Multi Shell Dt Information Analysis?

Hello everyone :smiling_face_with_three_hearts:

I am now working on a diffusion MRI research project and I am creating a large dataset using multi shell diffusion tensor imaging. Given the amount and complexity of information; I hope to create a strong and productive processing pathway.

A summary of the project
Dt information from several shells was acquired using three different b values
Every person has about 150 diffusion-weighted photos, as well as non diffusion images.
Investigate white matter stability and connectivity.
Use tract based spatial statistics and whole-brain tractography.

  • What are the best methods for preparing multi-shell Dt information for MRtrix? I am looking for guidance on noise reduction; removing Noise a sound; adjusting motion and waves, and adjusting discrimination fields. Are there any characteristics and setups that I should be aware of?
  • What is the best way to match the diffusion tensor model in MRtrix? Should I apply the dwi2tensor command directly; or is it better to apply more complex models like constrained spherical deconvolution?
  • What methods would you suggest to obtain the most correct and medically acceptable outcomes from tractography? Are there certain methods; seed methods that have been successful in previous research?
  • I am curious about creating structural connectomes. What are the best ways of creating and evaluating connectomes with MRtrix. Any suggestions for parcellation structures; related tests, and display methods?
  • Are there any connections with other neuroimaging tools such as FSL, free surfer that you have found particularly beneficial in your workflow?

While I have read information about this multi shell Dt information analysis there are some threads like this but I am looking for more detailed guidance from anyone who suggests advice on the optimal pathway for multi-shell Dt information analysis.

I would be grateful for any accurate advice, to relevant tutorials and information that would help me speed up my research. :slightly_smiling_face: Also; if anyone has worked with similar information sets, I would be interested in learning about the difficulties you faced and how you dealt with them.

Thanks in advance for your efforts :heart_hands: :pray: