Just a small addition here: as I’ve mentioned in this post just now, you can actually also continue using the multi-tissue pipeline after you’ve obtained the WM and CSF outcomes from dwi2fod msmt_csd. So essentially still dwi2response dhollander, ditching the GM response, dwi2fod msmt_csd with only WM and CSF responses, but then not ditching the CSF outcome, but proceeding with the multi-tissue pipeline (rather than the single-shell one) while using 2 tissue types (rather than the exemplary 3 in the documentation). The mtnormalise step should work quite well with WM and CSF, as long as they come from an actual 2-tissue WM-CSF reconstruction (so not from a 3-tissue WM-GM-CSF reconstruction where you ditch the GM; that would be ditching actual signal, which isn’t good for mtnormalise).
The reason why this still works very decently, is because the b=0 signal from GM is still not massively different from WM, and the non-b=0 signal will in most scenarios be the other way around. The CSF compartment will also still fit a tiny bit of the actual GM. So putting this all together, the summed WM+CSF image from a WM+CSF 2-tissue reconstruction, plus rebalancing (which mtnormalise does internally for you), still results in a quite flat image; apart from T2 shine-through and bias fields. That’s exactly the assumption that mtnormalise hinges on, so it does perform well in practice.