Multicenter dataset of multi-shell diffusion MRI in healthy traveling adults with identical settings

Abstract

Multicenter diffusion magnetic resonance imaging (MRI) has drawn great attention recently due to the expanding need for large-scale brain imaging studies, whereas the variability in MRI scanners and data acquisition tends to confound reliable individual-based analysis of diffusion measures. In addition, a growing number of multi-shell diffusion models have been shown with the potential to generate various estimates of physio-pathological information, yet their reliability and reproducibility in multicenter studies remain to be assessed. In this article, we describe a multi-shell diffusion dataset collected from three traveling subjects with identical acquisition settings in ten imaging centers. Both the scanner type and imaging protocol for anatomical and diffusion imaging were well controlled. This dataset is expected to replenish individual reproducible studies via multicenter collaboration by providing an open resource for advanced and novel microstructural and tractography modelling and quantification.

Brain/MINDS beyond human brain MRI project: A protocol for multi-level harmonization across brain disorders throughout the lifespan

“…This approach requires the images from the same participants at all the participating sites, but also requires significant effort from the sites and the participants when compared to other harmonization methods listed above, and the TS scans must be completed before the analysis starts. However, the TS approach can differentiate most of the sample variability from measurement bias in functional MRI ( Yamashita et al, 2019 ), structure and diffusion MRI ( Tong et al, 2020 ). In our prior study, by scanning nine TS participants repeatedly at all the twelve sites, Yamashita et al achieved the high-quality harmonization of the functional connectivity obtained by functional MRI ( Yamashita et al, 2019 ).…”

Style Transfer Using Generative Adversarial Networks for Multi-Site MRI Harmonization

“…We deliberately kept some cohorts overlapping completely in age, while others were non-overlapping. To show that our model generalizes to unseen images, we also applied the trained harmonization model to one travelling subject collected in (Tong et al, 2020), who was scanned 12 times at 10 different sites within 13 months. This traveling subject was also used to validate the harmonization quantitatively.…”

“…In these situations, the demographic and clinical conditions need to be strictly controlled and matched. Furthermore, even with the data collected from the same scanners/sites, the images collected may also show slight variance (Tong et al, 2020). These intra-site differences make the harmonization less accurate due to the lack of diversity of these domain-based methods.…”

Brain/MINDS Beyond Human Brain MRI Project: A Protocol for Multi-Site Harmonization across Brain Disorders Throughout the Lifespan

“…This approach requires the images from the same participants at all the participating sites, but also requires significant effort from the sites and the participants when compared to other harmonization methods listed above, and the TS scans must be completed before the analysis starts. However, the TS approach can differentiate most of the sample variability from measurement bias in functional MRI (Yamashita et al, 2019), structure and diffusion MRI (Tong et al, 2020). The DecNef Project explored rsfMRI functional connectivity for multiple psychiatric diseases and scanned nine TS participants who received repeated MRI measurements at all sites.…”