Hello,
I have been having issues with the alignment for some of my data (resting state rsfMRI to T1). It appears that this occurs once every 11 subjects, which is not ideal. A colleague has checked with SPM12 and found no issues on their end. Checking with afni (pb03....volreg file) and QC (attached the files: ve2a.jpg and ve2a_2.jpg for visual), it shows that the problem occurs after tcat and despike, and during the volume registration step.
This is my script:
afni_proc.py -subj_id Subj_5SS \
-blocks despike tshift align tlrc volreg blur mask regress \
-copy_anat /data2/open_data/ADNI/ADNI3///Subj_5SS/*Accel*.nii.gz \
-dsets /data2/open_data/ADNI/ADNI3///Subj_5SS/*MRI_E*.nii.gz \
-tcat_remove_first_trs 2 \
-align_opts_aea -cost lpc+ZZ \
-tlrc_base MNI_avg152T1+tlrc \
-tlrc_NL_warp \
-volreg_align_to MIN_OUTLIER \
-volreg_align_e2a \
-volreg_tlrc_warp \
-mask_epi_anat yes \
-volreg_warp_dxyz 3 \
-regress_motion_per_run \
-regress_anaticor_fast \
-regress_censor_motion 0.2 \
-regress_censor_outliers 0.05 \
-regress_apply_mot_types demean deriv \
-regress_est_blur_errts \
-regress_run_clustsim no \
-execute
I've tried changing "-volreg_align_to MIN_OUTLIER" to third or last and deleting "-volreg_align_e2a" (If I recall correctly, this causes afni to align a2e?); it did not make the final outcome any better.
I've also tried adding " -volreg_allin_auto_stuff -autoweight -warp shift_rotate \" after " -tlrc_NL_warp " when the program recommended I used autoweight.
Below is the @ss_review_basic output of this particular example:
subject ID : Subj_5SS
AFNI version : AFNI_19.2.01
AFNI package : linux_ubuntu_16_64
TR : 3.0
TRs removed (per run) : 2
num stim classes provided : 0
final anatomy dset : anat_final.Subj_5SS+tlrc.HEAD
final stats dset : NO_STATS
final errts dset : errts.Subj_5SS.fanaticor+tlrc.HEAD
final voxel resolution : 3.000000 3.000000 3.000000
motion limit : 0.2
num TRs above mot limit : 33
average motion (per TR) : 0.145185
average censored motion : 0.120185
max motion displacement : 0.659715
max censored displacement : 0.617789
outlier limit : 0.05
average outlier frac (TR) : 0.0078753
num TRs above out limit : 10
num runs found : 1
num TRs per run : 198
num TRs per run (applied) : 136
num TRs per run (censored): 62
fraction censored per run : 0.313131
TRs total (uncensored) : 198
TRs total : 136
degrees of freedom used : 17
degrees of freedom left : 119
TRs censored : 62
censor fraction : 0.313131
num regs of interest : 0
TSNR average : 237.344
global correlation (GCOR) : 0.0574289
anat/EPI mask Dice coef : 0.796392
blur estimates (ACF) : 0.664923 3.90318 12.9759
blur estimates (FWHM) : 0 0 0
I initially suspected that it may be because these brains have severe cortical atrophy, but only about half of the misaligned data were controls. I also have a couple brains that have slight misalignments (not as severe as the attached photos, but still concerning enough). Any suggestion is greatly appreciated. Thank you.
Edited 2 time(s). Last edit at 07/29/2019 02:09AM by Nshin96.
