Scalar metric-weighted tract endpoint mask

[Valerie Sydnor]

Hi Frank!

I am working with a custom thalamocortical autotrack tract atlas from our paper https://www.nature.com/articles/s41593-025-01991-6 :) The atlas comprises streamlines connecting the thalamus to cortical regions.

My goal is to 1. identify which voxels in the cortex are connected to the thalamus by streamlines in the atlas, and 2. to weight each cortical voxel by the average <scalar metric> of all streamlines that end in that voxel, with <scalar metric> being e.g. QA, MD, ISO, etc. Ideally, the output is a nifti file where each cortical voxel that has streamlines connecting it to the thalamus has a scalar value that is derived by averaging metrics of interest across those streamlines; voxels with no connectivity to thalamus have a 0. I'm thinking of this as a scalar metric-weighted track endpoint image.

I know that step 1 can be accomplished easily in DSI Studio, for example by saving a track density image of tract endpoints. However, I'm not sure how to accomplish step 2, which requires knowing which atlas streamlines end in each voxel and what their average <scalar metric> is. 

Is there any way to accomplish this in DSI Studio? Thanks for your help and guidance here!

Valerie

[Frank Yeh]

I will figure out the best solution for this task and get back to you.
Best,
Frank

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