Testretest reliability of FreeSurfer automated hippocampal subfield segmentation within and across scanners Abstract   The human hippocampus is vulnerable to a range of degenerative conditions and as such, accurate in vivo measurement of the hippocampus and hippocampal substructures via neuroimaging is of great interest for understanding mechanisms of disease as well as for use as a biomarker in clinical trials of novel therapeutics. Although total hippocampal volume can be measured relatively reliably, it is critical to understand how this reliability is affected by acquisition on different scanners, as multiple scanning platforms would likely be utilized in largescale clinical trials. This is particularly true for hippocampal subregional measurements, which have only relatively recently been measurable through common image processing platforms such as FreeSurfer. Accurate segmentation of these subregions is challenging due to their small size, magnetic resonance imaging (MRI) signal loss in medial temporal regions of the brain, and lack of contrast for delineation from standard neuroimaging procedures.  Here, we assess the testretest reliability of the FreeSurfer automated hippocampal subfield segmentation procedure using 2xe2x80xafS model scanners (a Siemens Trio and Prismafit Trio upgrade). T1weighted images were acquired for 11 generally healthy younger participants (two scans on the Trio and one scan on the Prismafit). Each scan was processed through the standard crosssectional stream and the recently released longitudinal pipeline in FreeSurfer v6.0 for hippocampal segmentation. Testretest reliability of the volumetric measures was examined for individual subfields as well as percent volume difference and Dice overlap among scans and intraclass correlation coefficients (ICC). Reliability was high in the molecular layer, dentate gyrus, and whole hippocampus with the inclusion of three time points with mean volume differences among scans less than 3%, overlap greater than 80%, and ICC u003e0.95. The parasubiculum and hippocampal fissure showed the least improvement in reliability with mean volume difference greater than 5%, overlap less than 70%, and ICC scores ranging from 0.78 to 0.89. Other subregions, including the CA regions, were stable in their mean volume difference and overlap ( 75% respectively) and showed improvement in reliability with the inclusion of three scans (ICCxe2x80xafu003exe2x80xaf0.9). Reliability was generally higher within scanner (TrioTrio), however, TrioPrismafit reliability was also high and did not exhibit an obvious bias. These results suggest that the FreeSurfer automated segmentation procedure is a reliable method to measure total as well as hippocampal subregional volumes and may be useful in clinical applications including as an endpoint for future clinical trials of conditions affecting the hippocampus.

Testretest reliability and sample size estimates after MRI scanner relocation Abstract   Objective  Many factors can contribute to the reliability and robustness of MRIderived metrics. In this study, we assessed the reliability and reproducibility of three MRI modalities after an MRI scanner was relocated to a new hospital facility.    Methods  Twenty healthy volunteers (12 females, mean age (standard deviation)xe2x80xafxe2x80xaf41 (11) years, age range 25xe2x80x9366) completed three MRI sessions. The first session (S1) was one week prior to the 3T GE HDxt scanner relocation. The second (S2) occurred nine weeks after S1 and at the new location; a third session (S3) was acquired 4 weeks after S2. At each session, we acquired structural T1weighted, pseudocontinuous arterial spin labelled, and diffusion tensor imaging sequences. We used longitudinal processing streams to create 12 summary MRI metrics, including total gray matter (GM), cortical GM, subcortical GM, white matter (WM), and lateral ventricle volume; mean cortical thickness; total surface area; average gray matter perfusion, and average diffusion tensor metrics along principal white matter pathways. We compared mean MRI values and variance at the old scanner location to multiple sessions at the new location using Bayesian multilevel regression models. Kfold cross validation allowed identification of important predictors. Wholebrain analyses were used to investigate any regional differences. Furthermore, we calculated withinsubject coefficient of variation (wsCV), intraclass correlation coefficient (ICC), and dice similarity index (SI) of cortical segmentations across scanner relocation and withinsite. Additionally, we estimated sample sizes required to robustly detect a 4% difference between two groups across MRI metrics.    Results  All global MRI metrics exhibited little mean difference and small variability (bar cortical gray matter perfusion) both across scanner relocation and withinsite repeat. T1and DTIderived tissue metrics showedxe2x80xaf xe2x80xaf0.80 and withinsubject coefficient of variation (wsCV)xe2x80xaf    Conclusion  Cortical gray matter perfusion was the most variable metric investigated (necessitating large sample sizes to identify group differences), with other metrics showing substantially less variability. Scanner relocation appeared to have a negligible effect on variability of the global MRI metrics tested. This manuscript reports withinsite testretest variability to act as a tool for calculating sample size in future investigations. Our results suggest that when all other parameters are held constant (e.g., sequence parameters and MRI processing), the effect of scanner relocation is indistinguishable from withinsite variability, but may need to be considered depending on the question being investigated.