Estimating the effect of a scanner upgrade on measures of grey matter structure for longitudinal designs

Longitudinal imaging studies are crucial for advancing the understanding of brain development over the lifespan. Thus, more and more studies acquire imaging data at multiple time points or with long follow-up intervals. In these studies changes to magnetic resonance imaging (MRI) scanners often become inevitable which may decrease the reliability of the MRI assessments and introduce biases. We therefore investigated the difference between MRI scanners with subsequent versions (3 Tesla Siemens Verio vs. Skyra) on the cortical and subcortical measures of grey matter in 116 healthy, young adults using the well-established longitudinal FreeSurfer stream for T1-weighted brain images. We found excellent between-scanner reliability for cortical and subcortical measures of grey matter structure (intra-class correlation coefficient > 0.8). Yet, paired t-tests revealed statistically significant differences in at least 67% of the regions, with percent differences around 2 to 4%, depending on the outcome measure. Offline correction for gradient distortions only slightly reduced these biases. Further, T1-imaging based quality measures reflecting gray-white matter contrast systematically differed between scanners. We conclude that scanner upgrades during a longitudinal study introduce bias in measures of cortical and subcortical grey matter structure. Therefore, before upgrading a MRI scanner during an ongoing study, researchers should prepare to implement an appropriate correction method for these effects. This dataset contains all the data necessary to reproduce the region-wise analyses in this manuscript. - qa_info.csv (manual quality control results) -mriqc_measures.csv (output from mriqc) - aseg_update.csv (aseg outputs from Skyra ND/Verio ND) - aparc_ct_update.csv (cortical thickness outputs from Skyra ND/Verio ND) - aparc_volume_update.csv (cortical volume outputs from Skyra ND/Verio ND) - aparc_area_update.csv (cortical area outputs from Skyra ND/Verio ND) - vol_unw.csv (aseg outputs from unwarped Skyra ND/Verio ND) - aparc_ct_unw.csv (cortical thickness outputs from unwarped Skyra ND/Verio ND) - aparc_ct_veriond_skyrad.csv (cortical thickness outputs from previous analysis Skyra D/Verio ND)

纵向成像研究对于深化对生命全程大脑发育的理解至关重要。因此，越来越多的研究在多个时间点或长追踪间隔内收集成像数据。在这些研究中，磁共振成像（MRI）扫描仪的更新往往不可避免，这可能会降低MRI评估的可靠性并引入偏差。因此，我们调查了使用已建立的纵向FreeSurfer流对T1加权脑图像进行皮质和皮质下灰质测量的116名健康年轻成人，以比较后续版本的MRI扫描仪（3特斯拉西门子Verio与Skyra）之间的差异。我们发现皮质和皮质下灰质结构测量（类内相关系数大于0.8）在扫描仪间具有优异的可靠性。然而，配对t检验显示，在至少67%的区域中存在统计学上显著的差异，差异百分比约为2至4%，具体取决于结果指标。仅对梯度畸变进行离线校正仅略微减少了这些偏差。此外，基于T1成像的反映灰白质对比度的质量指标在扫描仪间系统地存在差异。因此，我们得出结论，纵向研究中扫描仪的升级引入了皮质和皮质下灰质结构测量的偏差。因此，在进行中的研究期间升级MRI扫描仪之前，研究人员应准备实施适当的校正方法以消除这些影响。本数据集包含了重现该手册中区域分析所需的所有数据。

- qa_info.csv（手动质量控制结果）
-mriqc_measures.csv（mriqc的输出）
- aseg_update.csv（Skyra ND/Verio ND的aseg输出）
-aparc_ct_update.csv（Skyra ND/Verio ND的皮质厚度输出）
-aparc_volume_update.csv（Skyra ND/Verio ND的皮质体积输出）
-aparc_area_update.csv（Skyra ND/Verio ND的皮质面积输出）
-vol_unw.csv（未扭曲Skyra ND/Verio ND的aseg输出）
-aparc_ct_unw.csv（未扭曲Skyra ND/Verio ND的皮质厚度输出）
-aparc_ct_veriond_skyrad.csv（前次分析中Skyra D/Verio ND的皮质厚度输出）