TractoFlow with gradient echo fieldmaps / FUGUE?

We recently discovered the TractoFlow processing toolbox when I started thinking about updating our research center’s DTI processing pipeline. I’m wondering if there are any plans to expand its functionality from using the optional TOPUP-style unwarping with blip-up/down spin echo fieldmaps to using gradient echo fieldmaps? I realize most current fMRI research these days lean towards the TOPUP approach… We also regularly collect two phase direction-inverted fieldmap scans for nearly all our current projects. But… I have a really nice archival fMRI/DTI dataset from one of my NIMH R01 projects that we finished data collection back in 2013 or so. When we began collecting those data in 2008, we only collected the standard Siemens GE fieldmap. So I have a nice developmental cognitive neuroscience dataset that we’re actually interested in going back to explore some things using the DTI data… But would like to use the best DTI prep approach possible.

If adding a FUGUE-like optional unwarping step to TractoFlow might be in the works, please let me know? Alternatively, can anyone direct me to an authoritative source that discusses the pros/cons of using vs. not using an unwarping step compared to just trusting the nonlinear registration to the T1/T2 data? I’d like to read up on it if someone can make a good recommendation.

Thanks much,

Hi @mcstevens ,

Even if I completely understand the need you have for such feature, we are not planning on adding it to Tractoflow. If somebody would be willing to add it please go ahead we would more than happy to get other people involved in the project. I have no paper to suggest you but from my own experience a couple of years ago I was working on a similar project as Tractoflow and we used to run the unwarping step using fieldmaps and it was really helpful when registering the T1 to diffusion space.