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

Abstract

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 CO2 (PETCO2), 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 PETCO2 input models revealed that boxcar and ramp hypercapnia paradigms had the lowest relative deconvolution error. We used a T2* BOLD‐MRI sequence on a 3 T MRI scanner, with a boxcar delivery model of CO2, 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.

Cerebrovascular Reactivity Measurement Using Magnetic Resonance Imaging: A Systematic Review

“…Of the 142 articles reporting CVR measurements in pathology (referred to in Table 1), 70 studies assessed CVR to investigate pathophysiology, 48 studies explored the technical feasibility of a methodology to detect CVR impairment, 13 studies investigated the effect of a therapeutic intervention on CVR (surgical intervention for steno-occlusive diseases such as revascularisation, candesartan therapy for diabetes, bariatric surgery for obese subjects, haemodialysis for end-stage renal disease, therapeutic continuous positive airway pressure for obstructive sleep apnoea), six studies investigated the progression of pathologies, and five studies looked at the effect of CVR on fMRI BOLD activation. Relative to healthy controls, CVR was lower in patients in most of the pathologies (Krainik et al, 2005;Donahue et al, 2009;da Costa et al, 2016;Hartkamp et al, 2018;Thrippleton et al, 2018;McKetton et al, 2019) and CVR delays were longer in steno-occlusive diseases, small vessel disease and dementia (Hartkamp et al, 2012;Duffin et al, 2015;Thrippleton et al, 2018;Atwi et al, 2019;Holmes et al, 2020).…”

“…The delay between two signals can be found using linear regression or cross-correlation by determining the time shift giving the best correlation between these two signals. As with CVR computation, delay computation is an evolving area and new methods are arising including obtaining the delay directly from the HRF between the BOLD signal and EtCO 2 (Atwi et al, 2019). One study corrected the hypercapnic delay for delay due to the vasculature (i.e., the delay it takes for the blood and CO 2 to travel from the lungs to the brain tissues) by using the BOLD delay from a hyperoxia challenge as a surrogate of vasculature delay and assuming no vasodilation due to hyperoxia (Champagne et al, 2019a).…”

“…40% of the studies (93/235) calculated a whole brain or single region-of-interest delay that was applied to all voxels. While this method may be relatively robust against noise, delay is known to vary between and within tissue types (Thrippleton et al, 2018;Atwi et al, 2019). However, only 26% of studies (62/235) accounted for voxel-wise delays.…”

Decreased Cerebrovascular Reserve is the Initial Cause of White Matter Hyperintensity Related Cognitive Decline

“…Findings from BOLD-based CVR studies remain controversial [16]. Some studies reported whole brain CVR was not related to WMH [42,43], but others showed decreased CVR at baseline can predict the process of WMH lesions [18,44,45]. Based on previous studies, the current study con rmed that WMH was associated with decreased CVR again.…”

“…Impaired CVR is correlated closely with normal aging [13] and might be a sensitive early predictor of Alzheimer's disease [14]. In addition, it is reported that impaired CVR is the most reliable neuroimaging predictor of impending cerebrovascular disease [15,16], and could be a neuroimaging marker guiding the treatment and prevention of stroke and cerebral small vessel disease (CSVD) [17,18]. Furthermore, increasing evidences have demonstrated that CVR function is associated with subtle perfusion and microstructure changes in normal-appearing white matter (NAWM) [19], and has been involved in the pathophysiology disruption of the brain network connectome in individuals with WMH [20].…”