I am reanalyzing some pre-existing datasets with resting and task fMRI data and field maps. I used FMRIPREP for preprocessing and have several questions regarding the field maps:
- If I have EPI 4D volumes of different tasks scanned in the same scanning session (all the different task are acquired with the same scanning parameters) but only acquired one field map, could this one field map be applied to all the different task EPI datas? Or should each EPI 4D volume have its own corresponding field map?
- What if their are slight differences in the scanning parameters? For instance, I have a resting state scan with TR=2.1 and a task scan with TR=2, and all the other parameters are the same, could the same field map be applied to both the resting-state scan and the task scan?
- What about differences in image dimension? In another existing dataset, the voxels size in all the task 4D volumes and the field map are 3.516x3.516x3mm, but the image dimension of the EPI volumes are 64x64x36, and the field map’s image dimension is 64x64x38. Could this field map be used on these EPI data?
- Finally, what if the voxel dimensions are different? In another dataset, the image dimension of both the EPI and field maps are 64x64x36. However, the field map’s voxel dimension was 3.516x3.516x3mm, but the EPI volume has a higher voxel resolution with 3x3x3mm. Therefore the FOV are different between the EPI and the field map, but the transformation matrix stored in the nifti make the contour of the brain overlapped pretty well among the two. Could this field map still be used for this EPI?
I have tried all of the above with the FMRIPREP pipeline, and all of them performed the susceptibility distortion correction without raising error in the report.
I would like to ask whether the above preprocessing with SDC is acceptable?
Is the field map being estimated able to undergo interpolation to deal with the dimension difference?
Or should I just give up using the field map to do SDC when the TR, voxel dimension, or image dimension are not all exactly the same?
Thank you very much!