Midline Shift vs. MidSurface Shift: Correlation with Outcome of Traumatic Brain Injuries Traumatic brain injury (TBI) is a major health and socioeconomic problem globally that is associated with a high level of mortality. Early and accurate diagnosis and prognosis of TBI is important in patient management and preventing any secondary injuries. Computer tomography (CT) imaging assists physicians in diagnosing injury and guiding treatment. One of the clinical parameters extracted from CT images is midline shift, a measure of linear displacement in brain structure, which is correlated with TBI patient outcomes. However, only a tiny fraction of the overall tissue displacement is quantified through this parameter. In this paper, a novel measurement of overall midsurface shift is proposed that quantifies the total volume of brain tissue shifted across the midline. When compared to traditional midline shift, midsurface shift has a stronger correlation with TBI patient outcomes.

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.