Public Safety Announcement: Make sure that you fix your TE & TR if you’re acquiring multi-shell data using multiple acquisitions, and intend to fit any kind of diffusion model that invokes a parametric relationship between signal intensity and b-value. MSMT CSD is actually fine here if you’re careful, but I’ve seen it cause issues elsewhere.
Can we say that the FOV/TR for certain patients can be different because a few slices are added to include coverage of more brain regions?
Usually one would set the FoV for acceptable coverage of the largest head expected, and swallow the penalty of having some expty space around smaller heads, precisely because when applying a quantitative interpretation to the data, having matched acquisition parameters is far more important than whether or not you have some extra empty voxels.
If by “say” you’re referring to what one would write in a manuscript, my personal advice would be to make sure it is conveyed that this was a mistake, and that you have done what was possible to mitigate the issue, e.g. omitting extreme outliers from response function estimation / including variations in acquisition parameters as nuisance variables in a GLM.
Does anyone have any ideas whether there are any effects of longer repetition times after a particular cut-off?
In simplest terms this is a matter of the relationship in magnitude between T1 and TR. Once you’ve reached maybe TR > 5 x T1, you’re unlikely to measure a difference; but with multi-band TRs can be much shorter, and there are imperfect slice profile and subject motion effects.