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

DOI

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)

Identifier
DOI https://doi.org/10.17617/3.6b
Metadata Access https://edmond.mpg.de/api/datasets/export?exporter=dataverse_json&persistentId=doi:10.17617/3.6b
Provenance
Creator Beyer, Frauke
Publisher Edmond
Publication Year 2021
OpenAccess true
Contact fbeyer(at)cbs.mpg.de
Representation
Language English
Resource Type Dataset
Version 1
Discipline Other