ABSTRACTSimilarly to human population imaging, there are several well-founded motivations for animal population imaging, the most notable being the improvement of the validity of statistical results by pooling a sufficient number of animal data provided by different imaging centers. In this paper, we demonstrate the feasibility of such a multicenter animal study, sharing raw data from forty rats and processing pipelines between four imaging centers. As specific use case, we considered the estimation of T1 and T2 maps for the healthy rat brain at 7T. We quantitatively report about the variability observed across two data provider centers and evaluate the influence of image processing steps on the final maps, by using three fitting algorithms from three centers. Finally, to derive relaxation time values per brain area, two multi-atlas segmentation pipelines from different centers were executed on two different platforms. In this study, the impact of the acquisition was 2.21% (not significant) and 9.52% on T1 and T2 estimates while the impact of the data processing pipeline was not significant (1.04% and 3.33%, respectively). In addition, the computed normality values can serve as relaxometry reference maps to explore differences to animal models of pathologies.
Population imaging of synaptically released glutamate in mouse hippocampal slices
