Thanks for looking deeper into this. I am not sure yet about the software version. Looking in the json files I found a line SoftwareVersions": “syngo MR D13”. Also, the scanner is a Skyra, so it seems the bug, particularly causing the flip from PA to RL, was present in other models. I was informed that a field map was not acquired for this dataset (I am unsure about the reason for such a decision). Now, when performing dicom to nifti conversion using heudiconv, I got a fmap folder with a “dir-AP_epi” json file. But I think there is no real field map. For this particular dataset, my problem is that in some subjects MPRAGE and BOLD sequences have different phase encode directions (e.g., BOLD has “i” and MPRAGE has “j”). In your expertise, is this something that can happen?, and are can I compare (or combine as part of the same group) subjects that have just PA direction?
This means that the software version was VD13, the bug was present.
If there is no nifti image, this means that there is no data to use to calculate a fiedlmap and corrrect your bold images for susceptibility distorsion correction (SDC) .Otherwise, if your bold runs are with dir-PA and if there one volume with dir-AP in the map folder, then you could do SDC for such a dataset, with methods such as topup (FSL).
You don’t have to worry about the MPRAGE images as these are images acquired with very different sequences. MPRAGE sequence is a 3D acquisition whereas bold EPI images are 2D axial acquisition. If you MPRAGE has “j” , I would guess there the sequence must a been prescribed in coronal, meaning the the readout direction must have been in “IS” direction, the first phase encoding direction in “AP” and the second phase encoding direction in “RL”. But in general you don’t have to worry about the phase encoding direction of the MPRAGE images since usually you don’t do SDC for MPRAGE images.
In your case, if for your 200 subject you have a mix a PA and RL (which means the the Phase EncodingDirection" reads “i” (P>A) or “-j” (R>L) ) , I would advise to do SDC for this data with tools such as SynBOLD-DisCo. SDC is in general recommended for BOLD analyses. See http://linkinghub.elsevier.com/retrieve/pii/S1053811902912814this paper for example, even more for in your case where the images are distorted differently from subject to subject due to different acquisition settings with different phase encoding directions.
Ok, not good for the studies acquiring large dataset on those days, but thanks for confirming.
Thank you so much for this! This is probably where I needed to go, and I didn’t know exactly how to approach it. I am particularly concerned on how mixed encoding could introduce inconsistencies across subjects, affecting both data reliability and spatial fidelity. One last question: I am curious if there could be effects in the registration into structural data, identification of resting-state networks, and mapping of regions of interest given this variability, particularly since I have been told that it is better to approach the data as two separate groups (reducing sample size as a consequence). Do you know if the methods to apply targeted correction techniques, or harmonization strategies for distortion alignment (either across RL and PA groups) reduce the chances to affect statistical power in group-level analysis?
It is an interesting topic. One could look at the output metrics for all your subjects and see if the measures could be clustered in two groups, based on the phase encoding direction of the acquisitions. I am not an expert there, but if you think at this issue as an harmonization issue as it is done across sites, you may try statistical method such as Combat to harmonize your data.