Dear experts,
I am working on a project looking at changes over time in both white and grey matter in aging and neurodegeneration.
the available diffusion data have been acquired with low b-values (b values: 0; 1000; 64 directions; no blip-up/blip-down design) on a SIEMENS Trio scanner. Currently I have analyzed the data following a standard DTI pipeline (FSL + DTITK) and focused on white matter. I have to questions:
- Regarding the analysis in white matter: would it make sense to use MRtrix3Tissue + FBA pipeline to generate fibre cross-section and (maybe) fiber density metrics with these data? I think I would focus more to FC but I am not sure how accurate the metric could be in this context (i.e., low b values).
- Regarding the analysis in gray matter: I would like to perform an analysis similar to the one performed in Kelly et al 2022, Neuroimage (very nice paper!). I am in particular referring to use the tissue microstructural and free-water composition metrics. However, I am not sure to what extent my data would provide an adequate input for such approach.
Any consideration and suggestion would be very much appreciated!
All the best,
Nicola
Dear experts,
I am working on a project looking at changes over time in both white and grey matter in aging and neurodegeneration.
the available diffusion data have been acquired with low b-values (b values: 0; 1000; 64 directions; no blip-up/blip-down design) on a SIEMENS Trio scanner. Currently I have analyzed the data following a standard DTI pipeline (FSL + DTITK) and focused on white matter. I have to questions:
Any consideration and suggestion would be very much appreciated!
All the best,
Nicola