Hemodynamic timing in resting-state and breathing-task BOLD fMRI

Abstract

The blood flow response to a vasoactive stimulus demonstrates regional heterogeneity across both the healthy brain and in cerebrovascular pathology. The timing of a regional hemodynamic response is emerging as an important biomarker of cerebrovascular dysfunction, as well as a methodological confound within fMRI analyses. Previous research demonstrated that hemodynamic timing is more robustly characterized when a larger systemic vascular response is evoked by a breathing challenge, compared to when only spontaneous fluctuations in vascular physiology are present (i.e., in resting-state data). However, it is not clear whether hemodynamic delays in these two conditions are physiologically interchangeable, and how methodological signal-to-noise factors may limit their agreement. To address this, we generated whole-brain maps of hemodynamic delays in nine healthy adults. We assessed the agreement of voxelwise gray matter (GM) hemodynamic delays between two conditions: resting-state and breath-holding. We found that delay values demonstrated poor agreement when considering all GM voxels, but increasingly greater agreement when limiting analyses to voxels showing strong correlation with the GM mean time-series. Voxels showing the strongest agreement with the GM mean time-series were primarily located near large venous vessels, however these voxels explain some, but not all, of the observed agreement in timing. Increasing the degree of spatial smoothing of the fMRI data enhanced the correlation between individual voxel time-series and the GM mean time-series and did not substantially change the agreement in hemodynamic timing as a function of this relationship strength. These results suggest that signal-to-noise factors may be limiting the accuracy of voxelwise timing estimates and hence their agreement between the two data segments. In conclusion, caution must be taken when using voxelwise delay estimates from resting-state and breathing-task data interchangeably, and additional work is needed to evaluate their relative sensitivity and specificity to aspects of vascular physiology and pathology.

Dissecting Multiparametric Cerebral Hemodynamics using Integrated Ultrafast Ultrasound and Multispectral Photoacoustic Imaging

“…5) suggested a reproducible temporal pattern between the venous blood volume and overall CBV, which further agreed with previous findings using optical imaging [44] and fMRI [56]. However, optical imaging is not capable of mapping deep brain venous dynamics, while fMRI could not directly assess the venous rCBV change [56], setting fUSPA as a unique device for studying the temporal patterns of the single vessel in the deep brain, which is often assessed in sleep [57], and resting state studies [58]. Furthermore, fUSPA provided the multiparametric ULM based vertical speed map and MSPA based SO2 map that helped us confidently segment out the venous area, which was not achievable with fMRI alone.…”

Robust estimation of dynamic cerebrovascular reactivity using breath-holding fMRI: application in diabetes and hypertension

“…This latter alternative is easier to administer clinically than blood tagging while eliciting a generally robust BOLD response [Donahue et al, 2015]. Indeed, CVR-delay estimation is more robust when performed for a respiratory challenge than using resting-state data [Gong et al, 2023;Stickland et al, 2021;Zvolanek et al, 2023].…”