QSIRecon: What is the best reconstruction workflow for our dMRI dataset?

Hi developers,

Our clinical-grade DTI data have only 20 directions and a b-value of 1000, without reverse phase-encode collection. What is the best reconstruction workflow would you suggest for our dMRI data to do an automated fiber quantification? I searched this question with Google, and it suggested to use pyAFQ pipeline for these low-angular resolution data. Do you agree with this response?

At the same time, I also want to compute white matter free water measures along the segmented tracts. Do you think our data can fulfill this purpose?

Thanks for your advice in advance.

Best,

Angel

Hi @angelwong and welcome to neurostars!

I’d recommend the ss3t_fod_autotrack recon spec. See this paper for benchmarking: https://onlinelibrary.wiley.com/doi/abs/10.1002/hbm.70429

QSIRecon does not have a single-shell workflow for free water estimation. Although by running the autotrack recon spec above, you will still get a GQI fit on your data which quantifies (among other things) isotropic diffusion.

If you need tract profiles, you would need to use a PyAFQ pipeline. But as far as I know, you can only get profiles for certain common scalars (e.g., DTI and DKI measures), not any arbitrary scalar map (e.g. your free water measures). So in your case, no out-of-the-box QSIRecon spec will do everything you want.

Best,

Steven