Advice on ROI Resampling and Alignment for Tractography in DSI Studio

[Yaojie Huang]

Dear Dr. Yeh,

I am working on a project that involves resampling Julich probabilistic ROIs (originally in MNI space) to native diffusion space for analysis and tractography in DSI Studio. My current pipeline uses ANTs to first transform ROIs from MNI to native T1 (ACPC) space, then resamples these masks into native DWI space (using the preprocessed DWI from QSIPrep as the reference image). I apply a 0.3 threshold to binarize the probabilistic masks before resampling.

While this approach appears to work, I am unsure if there are best practices or specific recommendations to ensure optimal alignment and compatibility with DSI Studio. Additionally, I want to confirm that resampling using the DWI reference image aligns the masks to the b=0 volume, and that this approach is appropriate for use with DSI Studio’s segmentation and tractography workflows.

Do you have any advice or suggestions for improving this workflow, or common pitfalls I should watch out for when preparing ROI masks for DSI Studio?

Thank you very much for your time.

Sincerely,
Yaojie

[Frank Yeh]

The workflow looks good to me.
I would use the same.
Frank

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[Loïc Daumail]

Dear Dr. Yeh,

Would you have any advice on improving the segmentation outcome within dsi-studio? We tried to segment MT-PT tract, and there was only one streamline connecting both ROIs as an output.

Is it because this is a custom tract?

We had much better outcomes using pyAFQ by running tractography on a custom bundle of MT-PT. But we wanted to test the segmentation on dsi-studio to run a specific analysis using BUAN from dipy.

Thanks,

Best,

-Loïc

[Frank Yeh]

It would be helpful if you may explain the definition of MT and PT
here (also their anatomical definition).
If the connecting fibers are short range U-fibers, the tracking
settings and region settings may need adjustment.
Best regards,
Frank

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