RS-FetMRI: a MATLAB-SPM Based Tool for Pre-processing Fetal Resting-State fMRI Data

Fetal Frontolimbic Connectivity Prospectively Associates With Aggression in Toddlers

“…The present results must therefore be interpreted with caution and in the context of analytic limitations. First, fetal fMRI data are contaminated by large fetal movements, resulting in significant data loss; it is common to discard 35% to 56% of rsfMRI frames due to fetal motion ( 36 , 76 ). In the present study, some fetuses had as few as 100 frames of rsfMRI data.…”

“…Outside of motion-related challenges, fetal fMRI preprocessing presently requires a number of manual steps (e.g., selection of low-motion segments based on visual inspection, manual brain masking) that hold potential to introduce unmeasured bias. Several research groups are making directed efforts to automate and quantify the impact of different preprocessing steps ( 39 , 40 , 76 ), which will continue to enhance the rigor of fetal fMRI.…”

The maternal-fetal neurodevelopmental groundings of preterm birth risk

“…Resting State functional volumes were preprocessed using a baseline fetal rs-fMRI preprocessing pipeline [ 12 ] in Statistical Parametric Mapping (SPM) (SPM12, University College London, available at http://www.fil.ion.ucl.ac.uk/spm/ ). The baseline fetal rs-fMRI preprocessing pipeline included the following steps: i) manual spatial reorientation in correct SPM orientation and origin set; ii) with-in session realignment to a session-specific reference image; iii) 1st pass with-in session scrubbing procedure including frame-to-mean ( https://www.nitrc.org/projects/artifact_detect ) and frame-to-frame estimates of motion and calculation of signal intensity changes [ 13 , 14 ]; iv) visual inspection and exclusion of with-in session outlier volumes; v) with-in session specific reference image masking to exclude maternal abdominal tissue; vi) realignment and calculation of the between-session mean reference masked image from with-in session-specific reference masked images; vii) 1st between-session realignment of all functional volumes to the between-session mean reference masked image; viii) 2nd pass between-session scrubbing procedure and between-session outlier volume exclusion; ix) 2nd between-session realignment post-scrubbing; x) between-session mean reference abdominal skull- and body-stripping using a subject-specific brain segmentation procedure a) for creation of an inner fetal brain mask based on subject-specific GW fetal tissue class probability maps [ 15 ] and b) for calculation of the deformation parameters for spatial normalization to fetal subject-specific GW standard space; xi) fetal inner-brain masking, spatial normalization and smoothing with a 4 mm gaussian kernel of all functional volumes.…”

Maternal anxiety‐driven modulation of fetal limbic connectivity designs a backbone linking neonatal brain functional topology to socio‐emotional development in early childhood

“…Fetal scans were processed using the resting‐state fetal functional MRI (RS‐FetMRI) preprocessing pipeline (Pecco et al, 2022; https://github.com/NicoloPecco/RS-FetMRI)). The RS‐FetMRI is a fetal rs‐fMRI “structural‐free” preprocessing pipeline divided into six inter‐dependent preprocessing modules (i.e., M1–M6) including (i) functional time‐series conversion and fetal fMRI volume reorientation (M1); (ii) first pass masking, realignment and first pass scrubbing procedure (within session) (M2); (iii) within‐session reference volume segmentation and second pass masking with creation of the mean between‐session reference volume (M3); (iv) between‐session realignment and second pass scrubbing procedure (M4); (v) mean between‐session reference volume segmentation and spatial normalization (M5); and (vi) mean reference masking, spatial normalization, and smoothing of all functional volumes (M6) (see supplementary materials).…”

“…Fetal scans were processed using the resting-state fetal functional MRI (RS-FetMRI) preprocessing pipeline (Pecco et al, 2022;…”