BOLD-based cerebrovascular reactivity vascular transfer function isolates amplitude and timing responses to better characterize cerebral small vessel disease.

Cerebrovascular reactivity (CVR) is a dynamic measure of the cerebral blood vessel response to vasoactive stimulus. Conventional CVR measures amplitude changes in the blood-oxygenation-level-dependent (BOLD) signal per unit change in end-tidal CO (P CO ), effectively discarding potential timing information. This study proposes a deconvolution procedure to characterize CVR responses based on a vascular transfer function (VTF) that separates amplitude and timing CVR effects. We implemented the CVR-VTF to primarily evaluate normal-appearing white matter (WM) responses in those with a range of small vessel disease. Comparisons between simulations of P CO input models revealed that boxcar and ramp hypercapnia paradigms had the lowest relative deconvolution error. We used a T * BOLD-MRI sequence on a 3 T MRI scanner, with a boxcar delivery model of CO , to test the CVR-VTF approach in 18 healthy adults and three white matter hyperintensity (WMH) groups: 20 adults with moderate WMH, 12 adults with severe WMH, and 10 adults with genetic WMH (CADASIL). A subset of participants performed a second CVR session at a one-year follow-up. Conventional CVR, area under the curve of VTF (VTF-AUC), and VTF time-to-peak (VTF-TTP) were assessed in WM and grey matter (GM) at baseline and one-year follow-up. WMH groups had lower WM VTF-AUC compared with the healthy group (p < 0.0001), whereas GM CVR did not differ between groups (p > 0.1). WM VTF-TTP of the healthy group was less than that in the moderate WMH group (p = 0.016). Baseline VTF-AUC was lower than follow-up VTF-AUC in WM (p = 0.013) and GM (p = 0.026). The intraclass correlation for VTF-AUC in WM was 0.39 and coefficient of repeatability was 0.08 [%BOLD/mm Hg]. This study assessed CVR timing and amplitude information without applying model assumptions to the CVR response; this approach may be useful in the development of robust clinical biomarkers of CSVD.