Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy.
Department of Obstetrics and Gynecology, IRCCS Ospedale San Raffaele, Milan, Italy.
Neuroinformatics. 2022 Oct;20(4):1137-1154. doi: 10.1007/s12021-022-09592-5. Epub 2022 Jul 14.
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.
静息态功能磁共振成像(rs-fMRI)最近被证明为研究胎儿期功能神经发育提供了一个无限的窗口。胎儿大脑的激活和连接图谱可能会受到以下因素的强烈影响:1)胎儿特有的运动效应对时间序列的影响,2)时间序列空间归一化到标准化胎龄(GW)特定胎儿模板空间的准确性。由于缺乏标准化和可推广的图像处理协议,本研究的目的是实现一个经过验证的胎儿 rs-fMRI 预处理流水线(RS-FetMRI),该流水线分为 6 个相互依赖的预处理模块(即 M1 到 M6),旨在完全作为统计参数映射(SPM)的扩展。RS-FetMRI 流水线对从在 1.5T 和 3T MRI 扫描系统上采集的胎儿 rs-fMRI 时间序列进行输出分析,结果显示,在估计运动程度方面的效果得到了提高,同时还采用了有效的运动剔除程序,从而增加了运动未受干扰的体积数量和胎儿 rs-fMRI 时间序列数据的时间连续性。此外,一种“无结构”的基于 SPM 的空间归一化程序可以实现高度的空间重叠,具有高度的可重复性,并且在全脑和分割特异性时间信号到噪声比(TSNR)方面都有显著提高,这反映在功能连接分析中。据我们所知,RS-FetMRI 流水线是第一个半自动且易于使用的标准化胎儿 rs-fMRI 预处理流水线,完全集成在 MATLAB-SPM 中,能够为新的研究小组进入胎儿 rs-fMRI 领域消除障碍,无论是出于研究还是临床目的,最终使未来的胎儿大脑连接研究更适合比较和交叉验证。