Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI) most recently has proved to open a measureless window on functional neurodevelopment in utero. Fetal brain activation and connectivity maps can be heavily influenced by 1) fetal-specific motion effects on the time-series and 2) the accuracy of time-series spatial normalization to a standardized gestational-week (GW) specific fetal template space.
Due to the absence of a standardized and generalizable image processing protocol, the objective of the present work was to implement a validated fetal rs-fMRI preprocessing pipeline (RS-FetMRI) divided into 6 inter-dependent preprocessing modules (i.e., M1 to M6) and designed to work entirely as an extension for Statistical Parametric Mapping (SPM).
RS-FetMRI pipeline output analyses on rs-fMRI time-series sampled from a cohort of fetuses acquired on both 1.5 T and 3 T MRI scanning systems showed increased efficacy of estimation of the degree of movement coupled with an efficient motion censoring procedure, resulting in increased number of motion-uncorrupted volumes and temporal continuity in fetal rs-fMRI time-series data. Moreover, a “structural-free” SPM-based spatial normalization procedure granted a high degree of spatial overlap with high reproducibility and a significant improvement in whole-brain and parcellation-specific Temporal Signal-to-Noise Ratio (TSNR) mirrored by functional connectivity analysis.
To our knowledge, the RS-FetMRI pipeline is the first semi-automatic and easy-to-use standardized fetal rs-fMRI preprocessing pipeline completely integrated in MATLAB-SPM able to remove entry barriers for new research groups into the field of fetal rs-fMRI, for both research or clinical purposes, and ultimately to make future fetal brain connectivity investigations more suitable for comparison and cross-validation.
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Data and Code Availability
The entire RS-FetMRI preprocessing package is made available to the community through a GitHub open repository and it can be downloaded from (https://github.com/NicoloPecco/RS-FetMRI). The RS-FetMRI user manual can also be downloaded from (https://github.com/NicoloPecco/RS-FetMRI).
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Acknowledgements
The Authors would like to thank all of the pregnant women for their participation and their motivation and are very grateful to Prof. Ali Gholipour and the CRL group for the unmeasurable contribution to fetal brain imaging and for sharing the CRL Fetal Brain Atlas with the entire research community.
Funding
This study was supported by the Italian Ministry of Health’s “Ricerca Finalizzata 2016” (grant number RF-2016–02364081; Principal Investigator:Dr. Pasquale Anthony Della Rosa).
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The study protocol (number 39/OSR) was approved by the Ethics Committee of the San Raffaele Hospital and all women provided written informed consent prior to participating in this study.
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Pecco, N., Canini, M., Mosser, K.H.H. et al. RS-FetMRI: a MATLAB-SPM Based Tool for Pre-processing Fetal Resting-State fMRI Data. Neuroinform 20, 1137–1154 (2022). https://doi.org/10.1007/s12021-022-09592-5
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DOI: https://doi.org/10.1007/s12021-022-09592-5