Computational protocol: Vascular reactivity in small cerebral perforating arteries with 7 T phase contrast MRI – A proof of concept study

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Protocol publication

[…] Velocity reactivity (Rv) in the CSO and BG was calculated with a linear mixed effects (LME) model. We chose this since the velocity data had multiple levels (group and subject), and an ordinary least squares approach would have overestimated the confidence, since within-subject perforators are not independent from one another (, , ). The model was set to explain the change in Vmean with the change in PetCO2, the fitted slope being the parameter of interest (Rv=∂V∂PetCO2). Rv was converted to % change from baseline velocity after the fit. The LME model fits both a group effect and an effect per subject, allowing a portion of the variance to be explained explicitly by between subject differences, decreasing the residuals. It also allows the use of every detected perforator separately without averaging per subject, increasing the degrees of freedom (, , ). The LME model was fitted and tested for significance with the NLME package (R Core Team) in R (R Foundation for Statistical Computing).Since the MCA data consists of only the subject level, the LME model collapses to ordinary least squares. Therefore, the flow reactivity (Rφ) of the MCA was determined using an ordinary least squares approach. MATLAB was used to test Rφ for significance. The measured flow was taken as the input measurement and the measured PetCO2 was taken as regressor. The fitted slope, converted to % change from baseline flow, was taken as the measure for flow reactivity.Changes in Ndetected were tested for significance using paired Student's t-tests. For this study, a probability for type I errors (α) smaller than 0.05 was decided to be significant. The change in Ndetected was tested single-sided. […]

Pipeline specifications

Software tools lme4, nlme
Application Mathematical modeling
Chemicals Carbon Dioxide